A new hybrid simulated annealing-based genetic programming technique to predict the ultimate bearing capacity of piles

The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP) tree-based, and simulated annealing–GP or SA–GP for prediction of the ultimate-bearing capacity ( Q ult ) of the pile. The collected database cons...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Engineering with computers Jg. 37; H. 3; S. 2111 - 2127
Hauptverfasser:	Yong, Weixun, Zhou, Jian, Jahed Armaghani, Danial, Tahir, M. M., Tarinejad, Reza, Pham, Binh Thai, Van Huynh, Van
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.07.2021 Springer Nature B.V
Schlagworte:	Area CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer-Aided Engineering (CAD Control Cross-sections Driven piles Drop hammers Estimation Fuzzy logic Genetic algorithms Machine learning Math. Applications in Chemistry Mathematical and Computational Engineering Original Article Performance indices Pile bearing capacities Prediction models Predictions Sensitivity analysis Simulated annealing Systems Theory Hybrid SA–GP GP tree-based ANFIS Pile bearing capacity Predictive model
ISSN:	0177-0667, 1435-5663
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP) tree-based, and simulated annealing–GP or SA–GP for prediction of the ultimate-bearing capacity ( Q ult ) of the pile. The collected database consists of 50 driven piles properties with pile length, pile cross-sectional area, hammer weight, pile set and drop height as model inputs and Q ult as model output. Many GP and SA–GP models were constructed for estimating pile bearing capacity and the best models were selected using some performance indices. For comparison purposes, the ANFIS model was also applied to predict Q ult of the pile. It was observed that the developed models are able to provide higher prediction performance in the design of Q ult of the pile. Concerning the coefficient of correlation, and mean square error, the SA–GP model had the best values for both training and testing data sets, followed by the GP and ANFIS models, respectively. It implies that the neural-based predictive machine learning techniques like ANFIS are not as powerful as evolutionary predictive machine learning techniques like GP and SA–GP in estimating the ultimate-bearing capacity of the pile. Besides, GP and SA–GP can propose a formula for Q ult prediction which is a privilege of these models over the ANFIS predictive model. The sensitivity analysis also showed that the Q ult of pile looks to be more affected by pile cross-sectional area and pile set.
AbstractList	The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP) tree-based, and simulated annealing–GP or SA–GP for prediction of the ultimate-bearing capacity (Qult) of the pile. The collected database consists of 50 driven piles properties with pile length, pile cross-sectional area, hammer weight, pile set and drop height as model inputs and Qult as model output. Many GP and SA–GP models were constructed for estimating pile bearing capacity and the best models were selected using some performance indices. For comparison purposes, the ANFIS model was also applied to predict Qult of the pile. It was observed that the developed models are able to provide higher prediction performance in the design of Qult of the pile. Concerning the coefficient of correlation, and mean square error, the SA–GP model had the best values for both training and testing data sets, followed by the GP and ANFIS models, respectively. It implies that the neural-based predictive machine learning techniques like ANFIS are not as powerful as evolutionary predictive machine learning techniques like GP and SA–GP in estimating the ultimate-bearing capacity of the pile. Besides, GP and SA–GP can propose a formula for Qult prediction which is a privilege of these models over the ANFIS predictive model. The sensitivity analysis also showed that the Qult of pile looks to be more affected by pile cross-sectional area and pile set. The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP) tree-based, and simulated annealing–GP or SA–GP for prediction of the ultimate-bearing capacity ( Q ult ) of the pile. The collected database consists of 50 driven piles properties with pile length, pile cross-sectional area, hammer weight, pile set and drop height as model inputs and Q ult as model output. Many GP and SA–GP models were constructed for estimating pile bearing capacity and the best models were selected using some performance indices. For comparison purposes, the ANFIS model was also applied to predict Q ult of the pile. It was observed that the developed models are able to provide higher prediction performance in the design of Q ult of the pile. Concerning the coefficient of correlation, and mean square error, the SA–GP model had the best values for both training and testing data sets, followed by the GP and ANFIS models, respectively. It implies that the neural-based predictive machine learning techniques like ANFIS are not as powerful as evolutionary predictive machine learning techniques like GP and SA–GP in estimating the ultimate-bearing capacity of the pile. Besides, GP and SA–GP can propose a formula for Q ult prediction which is a privilege of these models over the ANFIS predictive model. The sensitivity analysis also showed that the Q ult of pile looks to be more affected by pile cross-sectional area and pile set.
Author	Zhou, Jian Jahed Armaghani, Danial Tarinejad, Reza Pham, Binh Thai Van Huynh, Van Tahir, M. M. Yong, Weixun
Author_xml	– sequence: 1 givenname: Weixun surname: Yong fullname: Yong, Weixun organization: School of Resources and Safety Engineering, Central South University, Kunming Prospecting Design Institute Of China Nonferrous Metals Industry Co., Ltd – sequence: 2 givenname: Jian surname: Zhou fullname: Zhou, Jian organization: School of Resources and Safety Engineering, Central South University – sequence: 3 givenname: Danial surname: Jahed Armaghani fullname: Jahed Armaghani, Danial email: danialjahedarmaghani@tdtu.edu.vn organization: Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University – sequence: 4 givenname: M. M. surname: Tahir fullname: Tahir, M. M. organization: Faculty of Civil Engineering, UTM Construction Research Centre, Institute for Smart, Infrastructure and Innovative Construction (ISIIC), Universiti Teknologi Malaysia – sequence: 5 givenname: Reza surname: Tarinejad fullname: Tarinejad, Reza organization: Faculty of Civil Engineering, University of Tabriz – sequence: 6 givenname: Binh Thai surname: Pham fullname: Pham, Binh Thai organization: Institute of Research and Development, Duy Tan University – sequence: 7 givenname: Van surname: Van Huynh fullname: Van Huynh, Van organization: Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University
BookMark	eNp9kMtKAzEUhoMoWC8v4CrgOprMZHJZingDwY2uQyZzpo1MM2OSIn2bPkufzNQKggtXIeT_Tv7znaDDMAZA6ILRK0apvE6U1kIQyjShVNcV0QdoxnjdkEaI-hDNKJOSUCHkMTpJ6Z1SVpfgDK1vcIBPvFi30XfbTfLL1WAzdNiGAHbwYU5am8p9DgGyd9vNFMd5tMtlecIZ3CL4jxXgPOIpQuddxnkBeDVkvyxztpsWbNxFnZ2s83mNxx5PfoB0ho56OyQ4_zlP0dv93evtI3l-eXi6vXkmrmY6E00dk71SjlvNK-esaLnr217yqhKN6hiovuWScaF7TZVjHe-07LhslBIa2voUXe7nluKlacrmfVzFUL40VcOVLhq0KCm1T7k4phShN6WszX4MOVo_GEbNTrTZizZFtPkWbXRBqz_oFMvycf0_VO-hNO30QPxt9Q_1Bejnlvs
CitedBy_id	crossref_primary_10_1007_s40098_024_01036_y crossref_primary_10_1155_2020_8855069 crossref_primary_10_1016_j_engappai_2023_106568 crossref_primary_10_3390_app12178468 crossref_primary_10_1016_j_apor_2024_104149 crossref_primary_10_1007_s41939_024_00415_5 crossref_primary_10_1007_s10462_021_10036_w crossref_primary_10_1007_s12145_024_01482_5 crossref_primary_10_1007_s40030_024_00852_y crossref_primary_10_1016_j_asoc_2023_110808 crossref_primary_10_1007_s40515_023_00291_5 crossref_primary_10_1007_s10462_024_11099_1 crossref_primary_10_1038_s41598_024_83784_8 crossref_primary_10_1007_s12517_022_09557_7 crossref_primary_10_1007_s10462_022_10140_5 crossref_primary_10_1016_j_istruc_2024_106039 crossref_primary_10_1155_2021_5586913 crossref_primary_10_1007_s00603_024_04094_z crossref_primary_10_1007_s40515_024_00411_9 crossref_primary_10_1007_s11440_023_01830_7 crossref_primary_10_1155_2022_7183700 crossref_primary_10_1007_s00521_021_06321_y crossref_primary_10_1061__ASCE_CO_1943_7862_0002327 crossref_primary_10_3390_su152216070 crossref_primary_10_1007_s10661_021_09269_7 crossref_primary_10_1007_s11053_020_09773_6 crossref_primary_10_1016_j_measurement_2024_114563 crossref_primary_10_3846_jcem_2024_21886 crossref_primary_10_1007_s00366_020_00997_x crossref_primary_10_1155_2023_8272566 crossref_primary_10_3390_app10051691 crossref_primary_10_3390_buildings14082273 crossref_primary_10_1007_s40098_024_01083_5 crossref_primary_10_1016_j_trgeo_2024_101288 crossref_primary_10_1108_JM2_12_2024_0410 crossref_primary_10_4018_IJCAC_2022010101 crossref_primary_10_1007_s11053_020_09714_3 crossref_primary_10_1007_s41939_023_00184_7 crossref_primary_10_1007_s10462_024_10772_9 crossref_primary_10_3390_buildings13051242 crossref_primary_10_1007_s41062_021_00631_9 crossref_primary_10_1016_j_oceaneng_2023_114724 crossref_primary_10_1016_j_trgeo_2022_100756 crossref_primary_10_1007_s10163_023_01785_7 crossref_primary_10_1007_s42461_021_00455_2 crossref_primary_10_3390_app10072364 crossref_primary_10_1016_j_engstruct_2022_114769 crossref_primary_10_1016_j_ijrmms_2021_104856 crossref_primary_10_3390_ma13051072 crossref_primary_10_3390_app10041486 crossref_primary_10_3390_app112210908 crossref_primary_10_1007_s40808_025_02540_7 crossref_primary_10_1038_s41598_025_13616_w
Cites_doi	10.1016/j.tust.2016.12.009 10.1016/j.measurement.2019.06.007 10.1007/s10064-016-0872-8 10.1007/s11053-019-09519-z 10.1007/s00521-016-2598-8 10.1007/s10064-019-01626-8 10.1007/s12665-015-4305-y 10.1007/s00366-015-0404-3 10.1007/s00366-019-00770-9 10.1007/s12517-015-1908-2 10.1007/s00366-019-00752-x 10.1007/s10706-017-0254-4 10.1007/s00366-019-00849-3 10.1007/s00500-018-3253-3 10.1016/j.ijrmms.2009.03.004 10.1007/s00603-016-1015-z 10.1007/s00366-018-00700-1 10.1007/s00500-018-3517-y 10.1007/s10706-017-0356-z 10.1007/s10064-017-1116-2 10.3390/app9061042 10.1155/2016/5104907 10.1016/j.ijmst.2013.08.018 10.1007/s40815-017-0324-z 10.1177/1475921718797949 10.1617/s11527-013-0039-z 10.1016/j.compgeo.2007.03.001 10.1007/s11069-015-1842-3 10.1016/j.ins.2011.07.026 10.1061/(ASCE)MT.1943-5533.0000154 10.1126/science.220.4598.671 10.1016/j.enggeo.2014.11.016 10.1016/j.cie.2014.05.010 10.1016/j.ijrmms.2013.08.004 10.1016/j.ijrmms.2014.03.003 10.3390/app9020243 10.1109/ACCESS.2019.2927632 10.1016/j.asoc.2010.06.009 10.1007/s12665-016-5524-6 10.1007/s00521-017-3007-7 10.1016/j.ssci.2019.05.046 10.1007/s00366-017-0542-x 10.1007/s10064-014-0687-4 10.1007/s00366-016-0455-0 10.1080/0305215X.2018.1439943 10.1080/19648189.2016.1246693 10.1016/j.measurement.2015.07.019 10.1016/j.eswa.2007.06.006 10.3390/app9142788 10.1016/j.acme.2013.02.007 10.1016/j.cageo.2010.09.002 10.1016/j.tafmec.2007.04.008 10.1080/15376494.2018.1430874 10.1016/j.ssci.2011.08.065 10.1061/(ASCE)0733-9410(1996)122:6(492) 10.1016/j.advengsoft.2018.04.004 10.1002/nag.1076 10.1016/j.nima.2005.05.069 10.1016/j.enconman.2013.06.031 10.1016/j.measurement.2014.08.007 10.1016/j.tust.2018.07.023 10.1061/(ASCE)CF.1943-5509.0001292 10.1016/j.ijrmms.2007.02.003 10.1016/j.eswa.2010.10.021 10.1177/0040517509355344 10.1002/qsar.200710043 10.1007/978-3-319-20883-1 10.1007/s00366-017-0545-7 10.1007/s10706-018-0445-7 10.1016/j.acme.2016.11.005 10.3390/app9214650 10.1016/j.prostr.2019.08.123 10.1061/(ASCE)CP.1943-5487.0000553 10.1109/21.256541 10.1108/02644401111118132 10.1016/j.compgeo.2010.11.008 10.1016/j.measurement.2018.04.057 10.1061/(ASCE)1090-0241(1998)124:12(1177) 10.1016/S1093-3263(01)00123-1 10.1016/j.enggeo.2018.03.023 10.3390/app9183715 10.1007/978-1-84628-663-6_3 10.1007/s00521-015-2078-6 10.3390/s17061344 10.1016/j.prostr.2019.08.122 10.1063/1.1699114 10.1016/j.tust.2018.08.029 10.1016/j.jhydrol.2015.08.025 10.1016/j.measurement.2019.04.081 10.1007/s00521-015-2072-z 10.1007/s00521-015-1890-3 10.1016/j.ijrmms.2016.07.028 10.1016/j.eswa.2008.11.019 10.1061/(ASCE)1090-0241(2008)134:7(1021) 10.2140/jomms.2010.5.735
ContentType	Journal Article
Copyright	Springer-Verlag London Ltd., part of Springer Nature 2020 Springer-Verlag London Ltd., part of Springer Nature 2020.
Copyright_xml	– notice: Springer-Verlag London Ltd., part of Springer Nature 2020 – notice: Springer-Verlag London Ltd., part of Springer Nature 2020.
DBID	AAYXX CITATION 3V. 7SC 7TB 7XB 8AL 8FD 8FE 8FG 8FK ABJCF ABUWG AFKRA ARAPS AZQEC BENPR BGLVJ CCPQU DWQXO FR3 GNUQQ HCIFZ JQ2 K7- KR7 L6V L7M L~C L~D M0N M7S P5Z P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PTHSS Q9U
DOI	10.1007/s00366-019-00932-9
DatabaseName	CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts Mechanical & Transportation Engineering Abstracts ProQuest Central (purchase pre-March 2016) Computing Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials - QC ProQuest Central ProQuest Technology Collection ProQuest One Community College ProQuest Central Korea Engineering Research Database ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database Civil Engineering Abstracts ProQuest Engineering Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Computing Database Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection ProQuest Central Basic
DatabaseTitle	CrossRef Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) Mechanical & Transportation Engineering Abstracts ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Engineering Collection ProQuest Central Korea ProQuest Central (New) Advanced Technologies Database with Aerospace Engineering Collection Advanced Technologies & Aerospace Collection Civil Engineering Abstracts ProQuest Computing Engineering Database ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition Materials Science & Engineering Collection Engineering Research Database ProQuest One Academic ProQuest Central (Alumni) ProQuest One Academic (New)
DatabaseTitleList	Computer Science Database
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Applied Sciences Engineering Computer Science
EISSN	1435-5663
EndPage	2127
ExternalDocumentID	10_1007_s00366_019_00932_9
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C -~X .86 .DC .VR 06D 0R~ 0VY 1N0 1SB 203 28- 29G 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 5GY 5QI 5VS 67Z 6NX 78A 8FE 8FG 8TC 8UJ 95- 95. 95~ 96X 9M8 AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJCF ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTAH ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BBWZM BDATZ BENPR BGLVJ BGNMA BPHCQ BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 DWQXO EBLON EBS EIOEI EJD ESBYG F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ ITM IWAJR IXC IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K6V K7- KDC KOV KOW L6V LAS LLZTM M0N M4Y M7S MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM P19 P62 P9O PF0 PQQKQ PROAC PT4 PT5 PTHSS Q2X QOK QOS R4E R89 R9I RHV RIG RNI RNS ROL RPX RSV RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 Y6R YLTOR Z45 Z5O Z7R Z7S Z7X Z7Z Z83 Z86 Z88 Z8M Z8N Z8T Z8W Z92 ZMTXR ZY4 ~A9 ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PQGLB 7SC 7TB 7XB 8AL 8FD 8FK FR3 JQ2 KR7 L7M L~C L~D PKEHL PQEST PQUKI PRINS Q9U
ID	FETCH-LOGICAL-c319t-90c17f88c4a942cca6b4cfbf7422658d1e8fb471469f908c1d4d97d4758869eb3
IEDL.DBID	RSV
ISICitedReferencesCount	75
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000574106600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0177-0667
IngestDate	Tue Dec 02 15:54:26 EST 2025 Sat Nov 29 06:25:17 EST 2025 Tue Nov 18 22:08:07 EST 2025 Fri Feb 21 02:48:34 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	3
Keywords	Hybrid SA–GP GP tree-based ANFIS Pile bearing capacity Predictive model
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c319t-90c17f88c4a942cca6b4cfbf7422658d1e8fb471469f908c1d4d97d4758869eb3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
PQID	2548900996
PQPubID	326339
PageCount	17
ParticipantIDs	proquest_journals_2548900996 crossref_citationtrail_10_1007_s00366_019_00932_9 crossref_primary_10_1007_s00366_019_00932_9 springer_journals_10_1007_s00366_019_00932_9
PublicationCentury	2000
PublicationDate	20210700 2021-07-00 20210701
PublicationDateYYYYMMDD	2021-07-01
PublicationDate_xml	– month: 7 year: 2021 text: 20210700
PublicationDecade	2020
PublicationPlace	London
PublicationPlace_xml	– name: London – name: Heidelberg
PublicationSubtitle	An International Journal for Simulation-Based Engineering
PublicationTitle	Engineering with computers
PublicationTitleAbbrev	Engineering with Computers
PublicationYear	2021
Publisher	Springer London Springer Nature B.V
Publisher_xml	– name: Springer London – name: Springer Nature B.V
References	Apostolopoulou, Armaghani, Bakolas (CR12) 2019; 17 Momeni, Nazir, Armaghani, Maizir (CR73) 2014; 57 Bunawan, Momeni, Armaghani, Rashid (CR5) 2018; 124 Gandomi, Alavi, Mirzahosseini, Nejad (CR88) 2010; 23 Gandomi, Yun, Alavi (CR112) 2013; 46 Kirkpatrick, Gelatt, Vecchi (CR93) 1983; 220 Gandomi, Alavi, Shadmehri, Sahab (CR94) 2013; 13 Emamgolizadeh, Bateni, Shahsavani (CR61) 2015; 529 Chen, Sarir, Bui (CR78) 2019 Cavaleri, Asteris, Psyllaki (CR11) 2019; 9 Goh (CR49) 1996; 122 Koopialipoor, Armaghani, Hedayat (CR28) 2018 Asteris, Tsaris, Cavaleri (CR10) 2016; 2016 CR48 Tonnizam Mohamad, Jahed Armaghani, Ghoroqi (CR57) 2017 Hasni, Alavi, Jiao, Lajnef (CR102) 2017; 17 Chen, Shi, Shariati (CR4) 2019; 30 Asteris, Roussis, Douvika (CR8) 2017; 17 Momeni, Armaghani, Fatemi, Nazir (CR53) 2018; 34 Smith (CR104) 1986 Hossein Alavi, Hossein Gandomi (CR100) 2011; 28 Harandizadeh, Toufigh, Toufigh (CR80) 2018 Zhou, Li, Mitri (CR38) 2018; 81 Khandelwal, Singh (CR22) 2013; 46 CR59 Asteris, Nozhati, Nikoo (CR32) 2018; 26 Zhou, Yang (CR20) 2007; 48 Asteris, Apostolopoulou, Skentou, Moropoulou (CR37) 2019; 24 Shahin, Jaksa (CR72) 2009 Chen, Hu, Huang, Fang (CR46) 2019; 18 Khandelwal, Armaghani, Faradonbeh (CR26) 2016; 75 Yang, Lan, Lu, Zhou (CR21) 2015; 185 Asadi, Eftekhari, Bagheripour (CR65) 2011; 11 Golbraikh, Tropsha (CR107) 2002; 20 Hajihassani, Jahed Armaghani, Kalatehjari (CR60) 2017 Yang, Zeng, Lan, Zhou (CR16) 2014; 69 Gandomi, Alavi, Ryan (CR91) 2015 Wang, Shi, Zhou, Qiu (CR41) 2018; 50 Smith (CR82) 1960; 86 Koza, Koza (CR56) 1992 Fallahpour, Wong, Olugu, Musa (CR105) 2017; 19 Asteris, Kolovos (CR33) 2019; 31 Asteris, Moropoulou, Skentou (CR36) 2019; 9 Koopialipoor, Murlidhar, Hedayat (CR43) 2019 Khandelwal, Armaghani, Faradonbeh (CR23) 2017; 33 Goble, Rausche, Moses (CR83) 1970 Gandomi, Alavi (CR86) 2011; 181 Asteris, Armaghani, Hatzigeorgiou (CR35) 2019; 24 Shao, Armaghani, Bejarbaneh (CR47) 2019 Zhou, Li, Mitri (CR29) 2015; 79 Baykasoğlu, Güllü, Çanakçı, Özbakır (CR63) 2008; 35 Zhou, Li, Shi (CR27) 2012; 50 Faradonbeh, Armaghani, Monjezi, Mohamad (CR69) 2016; 88 Mostafavi, Mostafavi, Jaafari, Hosseinpour (CR99) 2013; 74 Zhou, Li, Yang (CR31) 2019; 118 Admuthe, Apte (CR98) 2010; 80 Zhou, Koopialipoor, Murlidhar (CR30) 2019 Link, Yager, Anjos (CR85) 2005; 551 Hajihassani, Abdullah, Asteris, Armaghani (CR9) 2019; 9 Shirani Faradonbeh, Monjezi, Jahed Armaghani (CR68) 2016 Moayedi, Armaghani (CR74) 2018; 34 Ekici, Aksoy (CR96) 2011; 38 Armaghani, Mohamad, Momeni, Narayanasamy (CR51) 2015; 74 Salgado (CR81) 2008 Padmini, Ilamparuthi, Sudheer (CR52) 2008; 35 Mohamad, Li, Murlidhar (CR58) 2019 Kiefa (CR71) 1998; 124 CR3 Harandizadeh, Armaghani, Khari (CR76) 2019 Fellenius (CR84) 1984; 1 Mayerhof (CR1) 1976; 102 Jang (CR95) 1993; 23 Khari, Dehghanbandaki, Motamedi, Armaghani (CR6) 2019; 146 Beiki, Majdi, Givshad (CR64) 2013; 63 CR87 Armaghani, Mahdiyar, Hasanipanah (CR25) 2016; 49 Zhou, Bejarbaneh, Armaghani, Tahir (CR90) 2019 Fallahpour, Olugu, Musa (CR103) 2016; 27 Xu, Gordan, Koopialipoor (CR45) 2019; 7 Fallahpour, Olugu, Musa (CR106) 2017; 28 Metropolis, Rosenbluth, Rosenbluth (CR92) 1953; 21 Li, Dai, Hou, Lei (CR62) 2007; 44 Zhou, Li, Mitri (CR42) 2016; 30 Jahed Armaghani, Hajihassani, Monjezi (CR54) 2015; 8 Kurugodu, Bordoloi, Hong (CR101) 2018; 122 Hasanipanah, Monjezi, Shahnazar (CR7) 2015; 75 Roy, Roy (CR109) 2008; 27 Xu, Zhou, Asteris (CR14) 2019; 9 Mollahasani, Alavi, Gandomi (CR108) 2011; 38 Gandomi, Alavi, Arjmandi (CR89) 2010; 5 Armaghani, Hatzigeorgiou, Karamani (CR15) 2019; 17 Pal, Deswal (CR50) 2008; 134 Momeni (CR2) 2012 Jahed Armaghani, Hasanipanah, Mahdiyar (CR39) 2018; 29 Samui (CR77) 2012; 36 Khandelwal, Singh (CR44) 2009; 46 Asteris, Kolovos, Douvika, Roinos (CR34) 2016; 20 Armaghani, Bin, Faizi, Rashid (CR75) 2017; 28 Zandi, Shariati, Marto (CR24) 2018; 28 Yang, Li, Jie, Zhang (CR19) 2018; 81 Ravandi, Rahmannejad, Monfared, Ravandi (CR67) 2013; 23 Faradonbeh, Jahed Armaghani, Monjezi (CR70) 2016 Chen, Asteris, Jahed Armaghani (CR13) 2019; 9 Karakus (CR66) 2011; 37 Ghorbani, Sadrossadat, Bazaz, Oskooei (CR79) 2018; 36 Yang, Xing, Wang, Li (CR18) 2018; 239 Armaghani, Mohamad, Narayanasamy (CR111) 2017; 63 Mousavi, Mostafavi, Hosseinpour (CR110) 2014; 74 Koopialipoor, Jahed Armaghani, Haghighi, Ghaleini (CR17) 2019; 78 Armaghani, Momeni, Abad, Khandelwal (CR55) 2015; 74 Zhou, Li, Wang (CR40) 2019; 33 Wu, Hsu, Chen (CR97) 2009; 36 DJ Armaghani (932_CR15) 2019; 17 RS Faradonbeh (932_CR69) 2016; 88 GG Mayerhof (932_CR1) 1976; 102 932_CR3 PP Roy (932_CR109) 2008; 27 R Shirani Faradonbeh (932_CR68) 2016 M Karakus (932_CR66) 2011; 37 SM Mousavi (932_CR110) 2014; 74 AH Gandomi (932_CR89) 2010; 5 J-S Jang (932_CR95) 1993; 23 M Khandelwal (932_CR22) 2013; 46 RS Faradonbeh (932_CR70) 2016 HQ Yang (932_CR18) 2018; 239 J Zhou (932_CR42) 2016; 30 932_CR48 AH Gandomi (932_CR112) 2013; 46 J Zhou (932_CR38) 2018; 81 PG Asteris (932_CR10) 2016; 2016 E Momeni (932_CR73) 2014; 57 B Chen (932_CR46) 2019; 18 M Pal (932_CR50) 2008; 134 L Cavaleri (932_CR11) 2019; 9 HQ Yang (932_CR16) 2014; 69 J-D Wu (932_CR97) 2009; 36 B Ghorbani (932_CR79) 2018; 36 R Salgado (932_CR81) 2008 H Hasni (932_CR102) 2017; 17 HV Kurugodu (932_CR101) 2018; 122 M Koopialipoor (932_CR28) 2018 AH Gandomi (932_CR88) 2010; 23 P Asteris (932_CR8) 2017; 17 AR Bunawan (932_CR5) 2018; 124 J Zhou (932_CR90) 2019 DJ Armaghani (932_CR25) 2016; 49 M Khandelwal (932_CR26) 2016; 75 E Tonnizam Mohamad (932_CR57) 2017 DJ Armaghani (932_CR51) 2015; 74 A Fallahpour (932_CR105) 2017; 19 M Apostolopoulou (932_CR12) 2019; 17 D Jahed Armaghani (932_CR54) 2015; 8 A Baykasoğlu (932_CR63) 2008; 35 A Fallahpour (932_CR106) 2017; 28 M Hasanipanah (932_CR7) 2015; 75 S Kirkpatrick (932_CR93) 1983; 220 N Metropolis (932_CR92) 1953; 21 M Koopialipoor (932_CR17) 2019; 78 M Hajihassani (932_CR9) 2019; 9 M Hajihassani (932_CR60) 2017 H Chen (932_CR13) 2019; 9 HQ Yang (932_CR21) 2015; 185 LS Admuthe (932_CR98) 2010; 80 PG Asteris (932_CR35) 2019; 24 H Harandizadeh (932_CR76) 2019 932_CR59 A Mollahasani (932_CR108) 2011; 38 M Khandelwal (932_CR44) 2009; 46 M Beiki (932_CR64) 2013; 63 AH Gandomi (932_CR86) 2011; 181 MAA Kiefa (932_CR71) 1998; 124 W Chen (932_CR78) 2019 GN Smith (932_CR104) 1986 EG Ravandi (932_CR67) 2013; 23 BB Ekici (932_CR96) 2011; 38 JM Link (932_CR85) 2005; 551 J Zhou (932_CR31) 2019; 118 932_CR87 Z Shao (932_CR47) 2019 H Moayedi (932_CR74) 2018; 34 MA Shahin (932_CR72) 2009 A Hossein Alavi (932_CR100) 2011; 28 H Xu (932_CR14) 2019; 9 M Khari (932_CR6) 2019; 146 C Chen (932_CR4) 2019; 30 XP Zhou (932_CR20) 2007; 48 J Zhou (932_CR29) 2015; 79 A Fallahpour (932_CR103) 2016; 27 M Khandelwal (932_CR23) 2017; 33 P Samui (932_CR77) 2012; 36 H Harandizadeh (932_CR80) 2018 J Zhou (932_CR40) 2019; 33 S Emamgolizadeh (932_CR61) 2015; 529 AH Gandomi (932_CR94) 2013; 13 W-X Li (932_CR62) 2007; 44 PG Asteris (932_CR33) 2019; 31 Y Zandi (932_CR24) 2018; 28 PG Asteris (932_CR37) 2019; 24 DJ Armaghani (932_CR55) 2015; 74 C Xu (932_CR45) 2019; 7 HQ Yang (932_CR19) 2018; 81 D Jahed Armaghani (932_CR39) 2018; 29 PG Asteris (932_CR36) 2019; 9 ET Mohamad (932_CR58) 2019 AH Gandomi (932_CR91) 2015 GG Goble (932_CR83) 1970 E Momeni (932_CR2) 2012 M Asadi (932_CR65) 2011; 11 DJ Armaghani (932_CR75) 2017; 28 EAL Smith (932_CR82) 1960; 86 JR Koza (932_CR56) 1992 ES Mostafavi (932_CR99) 2013; 74 DJ Armaghani (932_CR111) 2017; 63 PG Asteris (932_CR34) 2016; 20 M Wang (932_CR41) 2018; 50 E Momeni (932_CR53) 2018; 34 ATC Goh (932_CR49) 1996; 122 J Zhou (932_CR27) 2012; 50 A Golbraikh (932_CR107) 2002; 20 J Zhou (932_CR30) 2019 BH Fellenius (932_CR84) 1984; 1 PG Asteris (932_CR32) 2018; 26 D Padmini (932_CR52) 2008; 35 M Koopialipoor (932_CR43) 2019
References_xml	– volume: 17 start-page: 924 year: 2019 end-page: 933 ident: CR15 article-title: Soft computing-based techniques for concrete beams shear strength publication-title: Procedia Struct Integr – volume: 74 start-page: 120 year: 2014 end-page: 128 ident: CR110 article-title: Gene expression programming as a basis for new generation of electricity demand prediction models publication-title: Comput Ind Eng – volume: 118 start-page: 505 year: 2019 end-page: 518 ident: CR31 article-title: Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories publication-title: Saf Sci – volume: 63 start-page: 29 year: 2017 end-page: 43 ident: CR111 article-title: Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition publication-title: Tunn Undergr Sp Technol doi: 10.1016/j.tust.2016.12.009 – volume: 24 start-page: 469 year: 2019 end-page: 488 ident: CR35 article-title: Predicting the shear strength of reinforced concrete beams using artificial neural networks publication-title: Comput Concr – year: 2019 ident: CR47 article-title: Estimating the friction angle of black shale core specimens with hybrid-ANN approaches publication-title: Measurement doi: 10.1016/j.measurement.2019.06.007 – volume: 134 start-page: 1021 year: 2008 end-page: 1024 ident: CR50 article-title: Modeling pile capacity using support vector machines and generalized regression neural network publication-title: J Geotech Geoenviron Eng – volume: 23 start-page: 733 year: 2013 end-page: 737 ident: CR67 article-title: Application of numerical modeling and genetic programming to estimate rock mass modulus of deformation publication-title: Int J Min Sci Technol – volume: 20 start-page: 269 year: 2002 end-page: 276 ident: CR107 article-title: Beware of q2! publication-title: J Mol Graph Model – year: 2016 ident: CR70 article-title: Development of a new model for predicting flyrock distance in quarry blasting: a genetic programming technique publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-016-0872-8 – volume: 9 start-page: 243 year: 2019 ident: CR36 article-title: Stochastic vulnerability assessment of masonry structures: concepts, modeling and restoration aspects publication-title: Appl Sci – volume: 102 start-page: 11962 year: 1976 ident: CR1 article-title: Bearing capacity and settlemtn of pile foundations publication-title: J Geotech Geoenviron Eng – year: 2015 ident: CR91 publication-title: Handbook of genetic programming applications – volume: 239 start-page: 119 year: 2018 end-page: 125 ident: CR18 article-title: Model test on the entrainment phenomenon and energy conversion mechanism of flow-like landslides publication-title: Eng Geol – year: 2019 ident: CR30 article-title: Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance publication-title: Nat Resour Res doi: 10.1007/s11053-019-09519-z – volume: 146 start-page: 110 year: 2019 end-page: 118 ident: CR6 article-title: Computational estimation of lateral pile displacement in layered sand using experimental data publication-title: Measurement – volume: 44 start-page: 954 year: 2007 end-page: 961 ident: CR62 article-title: Fuzzy genetic programming method for analysis of ground movements due to underground mining publication-title: Int J Rock Mech Min Sci – volume: 81 start-page: 112 year: 2018 end-page: 120 ident: CR19 article-title: Effects of joints on the cutting behavior of disc cutter running on the jointed rock mass publication-title: Tunn Undergr Sp Technol – volume: 30 start-page: 457 year: 2019 end-page: 469 ident: CR4 article-title: Behavior of steel storage pallet racking connection—a review publication-title: Steel Compos Struct – volume: 28 start-page: 439 year: 2018 end-page: 447 ident: CR24 article-title: Computational investigation of the comparative analysis of cylindrical barns subjected to earthquake publication-title: Steel Compos Struct – volume: 30 start-page: 4016003 year: 2016 ident: CR42 article-title: Classification of rockburst in underground projects: comparison of ten supervised learning methods publication-title: J Comput Civ Eng – volume: 11 start-page: 1932 year: 2011 end-page: 1937 ident: CR65 article-title: Evaluating the strength of intact rocks through genetic programming publication-title: Appl Soft Comput – volume: 36 start-page: 1434 year: 2012 end-page: 1439 ident: CR77 article-title: Determination of ultimate capacity of driven piles in cohesionless soil: a multivariate adaptive regression spline approach publication-title: Int J Numer Anal Methods Geomech – volume: 185 start-page: 20 year: 2015 end-page: 32 ident: CR21 article-title: A quasi-three-dimensional spring-deformable-block model for runout analysis of rapid landslide motion publication-title: Eng Geol – volume: 69 start-page: 59 year: 2014 end-page: 66 ident: CR16 article-title: Analysis of the excavation damaged zone around a tunnel accounting for geostress and unloading publication-title: Int J Rock Mech Min Sci – volume: 28 start-page: 391 year: 2017 end-page: 405 ident: CR75 article-title: Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles publication-title: Neural Comput Appl – volume: 33 start-page: 4019024 year: 2019 ident: CR40 article-title: Feasibility of stochastic gradient boosting approach for evaluating seismic liquefaction potential based on SPT and CPT case histories publication-title: J Perform Constr Facil – volume: 29 start-page: 619 year: 2018 end-page: 629 ident: CR39 article-title: Airblast prediction through a hybrid genetic algorithm-ANN model publication-title: Neural Comput Appl doi: 10.1007/s00521-016-2598-8 – year: 1992 ident: CR56 publication-title: Genetic programming: on the programming of computers by means of natural selection – year: 2019 ident: CR90 article-title: Forecasting of TBM advance rate in hard rock condition based on artificial neural network and genetic programming techniques publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-019-01626-8 – volume: 74 start-page: 2845 year: 2015 end-page: 2860 ident: CR55 article-title: Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting publication-title: Environ Earth Sci doi: 10.1007/s12665-015-4305-y – volume: 23 start-page: 665 year: 1993 end-page: 685 ident: CR95 article-title: ANFIS: adaptive-network-based fuzzy inference system publication-title: IEEE Trans Syst Man Cybern – volume: 20 start-page: s102 year: 2016 end-page: s122 ident: CR34 article-title: Prediction of self-compacting concrete strength using artificial neural networks publication-title: Eur J Environ Civ Eng – volume: 50 start-page: 629 issue: 4 year: 2012 end-page: 644 ident: CR27 article-title: Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines publication-title: Safe Sci – volume: 122 start-page: 492 year: 1996 end-page: 495 ident: CR49 article-title: Pile driving records reanalyzed using neural networks publication-title: J Geotech Eng – year: 2016 ident: CR68 article-title: Genetic programing and non-linear multiple regression techniques to predict backbreak in blasting operation publication-title: Eng Comput doi: 10.1007/s00366-015-0404-3 – year: 2019 ident: CR58 article-title: The effects of ABC, ICA, and PSO optimization techniques on prediction of ripping production publication-title: Eng Comput doi: 10.1007/s00366-019-00770-9 – volume: 35 start-page: 111 year: 2008 end-page: 123 ident: CR63 article-title: Prediction of compressive and tensile strength of limestone via genetic programming publication-title: Expert Syst Appl – volume: 86 start-page: 35 year: 1960 end-page: 61 ident: CR82 article-title: Pile driving analysis by the wave equation publication-title: J Soil Mech ASCE – year: 2012 ident: CR2 publication-title: Axial bearing capacity of piles and modelling of distribution of skin resistance with depth – volume: 88 start-page: 254 year: 2016 end-page: 264 ident: CR69 article-title: Genetic programming and gene expression programming for flyrock assessment due to mine blasting publication-title: Int J Rock Mech Min Sci – volume: 9 start-page: 3715 year: 2019 ident: CR14 article-title: Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate publication-title: Appl Sci – volume: 8 start-page: 9647 year: 2015 end-page: 9665 ident: CR54 article-title: Application of two intelligent systems in predicting environmental impacts of quarry blasting publication-title: Arab J Geosci doi: 10.1007/s12517-015-1908-2 – volume: 80 start-page: 841 year: 2010 end-page: 846 ident: CR98 article-title: Adaptive neuro-fuzzy inference system with subtractive clustering: a model to predict fiber and yarn relationship publication-title: Text Res J – volume: 27 start-page: 707 year: 2016 end-page: 725 ident: CR103 article-title: An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach publication-title: Neural Comput Appl – volume: 27 start-page: 302 year: 2008 end-page: 313 ident: CR109 article-title: On some aspects of variable selection for partial least squares regression models publication-title: QSAR Comb Sci – ident: CR3 – volume: 9 start-page: 2788 year: 2019 ident: CR11 article-title: Prediction of surface treatment effects on the tribological performance of tool steels using artificial neural networks publication-title: Appl Sci – volume: 31 start-page: 409 year: 2019 end-page: 424 ident: CR33 article-title: Self-compacting concrete strength prediction using surrogate models publication-title: Neural Comput Appl – volume: 2016 start-page: 20 year: 2016 ident: CR10 article-title: Prediction of the fundamental period of infilled RC frame structures using artificial neural networks publication-title: Comput Intell Neurosci – volume: 74 start-page: 1301 year: 2015 end-page: 1319 ident: CR51 article-title: An adaptive neuro-fuzzy inference system for predicting unconfined compressive strength and Young’s modulus: a study on Main Range granite publication-title: Bull Eng Geol Environ – volume: 181 start-page: 5227 year: 2011 end-page: 5239 ident: CR86 article-title: Multi-stage genetic programming: a new strategy to nonlinear system modeling publication-title: Inf Sci (Ny) – volume: 81 start-page: 632 year: 2018 end-page: 659 ident: CR38 article-title: Evaluation method of rockburst: state-of-the-art literature review publication-title: Tunn Undergr Sp Technol – volume: 19 start-page: 1041 year: 2017 end-page: 1057 ident: CR105 article-title: A predictive integrated genetic-based model for supplier evaluation and selection publication-title: Int J Fuzzy Syst – volume: 36 start-page: 7809 year: 2009 end-page: 7817 ident: CR97 article-title: An expert system of price forecasting for used cars using adaptive neuro-fuzzy inference publication-title: Expert Syst Appl – volume: 122 start-page: 50 year: 2018 end-page: 61 ident: CR101 article-title: Genetic programming for soil-fiber composite assessment publication-title: Adv Eng Softw – volume: 17 start-page: 914 year: 2019 end-page: 923 ident: CR12 article-title: Compressive strength of natural hydraulic lime mortars using soft computing techniques publication-title: Procedia Struct Integr – volume: 46 start-page: 1214 year: 2009 end-page: 1222 ident: CR44 article-title: Prediction of blast-induced ground vibration using artificial neural network publication-title: Int J Rock Mech Min Sci – volume: 38 start-page: 5352 year: 2011 end-page: 5358 ident: CR96 article-title: Prediction of building energy needs in early stage of design by using ANFIS publication-title: Expert Syst Appl – start-page: 26 year: 2009 end-page: 33 ident: CR72 article-title: Intelligent computing for predicting axial capacity of drilled shafts publication-title: International foundation congress and equipment expo (IFCEE’09) – ident: CR87 – volume: 36 start-page: 2057 year: 2018 end-page: 2076 ident: CR79 article-title: Numerical ANFIS-based formulation for prediction of the ultimate axial load bearing capacity of piles through CPT data publication-title: Geotech Geol Eng – volume: 57 start-page: 122 year: 2014 end-page: 131 ident: CR73 article-title: Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN publication-title: Measurement – volume: 37 start-page: 1318 year: 2011 end-page: 1323 ident: CR66 article-title: Function identification for the intrinsic strength and elastic properties of granitic rocks via genetic programming (GP) publication-title: Comput Geosci – volume: 28 start-page: 242 year: 2011 end-page: 274 ident: CR100 article-title: A robust data mining approach for formulation of geotechnical engineering systems publication-title: Eng Comput – year: 2019 ident: CR78 article-title: Neuro-genetic, neuro-imperialism and genetic programing models in predicting ultimate bearing capacity of pile publication-title: Eng Comput doi: 10.1007/s00366-019-00752-x – year: 1970 ident: CR83 publication-title: Dynamics studies on the bearing capacity of piles: final report to the Ohio Department of Highways – volume: 529 start-page: 1590 year: 2015 end-page: 1600 ident: CR61 article-title: Estimation of soil cation exchange capacity using genetic expression programming (GEP) and multivariate adaptive regression splines (MARS) publication-title: J Hydrol – volume: 551 start-page: 504 year: 2005 end-page: 527 ident: CR85 article-title: Application of genetic programming to high energy physics event selection publication-title: Nucl Instruments Methods Phys Res Sect A Accel Spectrometers Detect Assoc Equip – volume: 33 start-page: 45 year: 2017 end-page: 53 ident: CR23 article-title: Classification and regression tree technique in estimating peak particle velocity caused by blasting publication-title: Eng Comput – year: 2017 ident: CR57 article-title: Ripping production prediction in different weathering zones according to field data publication-title: Geotech Geol Eng doi: 10.1007/s10706-017-0254-4 – year: 1986 ident: CR104 publication-title: Probability and statistics in civil engineering – volume: 28 start-page: 499 year: 2017 end-page: 504 ident: CR106 article-title: A hybrid model for supplier selection: integration of AHP and multi expression programming (MEP) publication-title: Neural Comput Appl – volume: 75 start-page: 739 year: 2016 ident: CR26 article-title: A new model based on gene expression programming to estimate air flow in a single rock joint publication-title: Environ Earth Sci – volume: 17 start-page: 609 year: 2017 end-page: 622 ident: CR102 article-title: Detection of fatigue cracking in steel bridge girders: a support vector machine approach publication-title: Arch Civ Mech Eng – volume: 18 start-page: 1355 year: 2019 end-page: 1371 ident: CR46 article-title: A spatio-temporal clustering and diagnosis method for concrete arch dams using deformation monitoring data publication-title: Struct Heal Monit – volume: 5 start-page: 735 year: 2010 end-page: 753 ident: CR89 article-title: Genetic programming and orthogonal least squares: a hybrid approach to modeling the compressive strength of CFRP-confined concrete cylinders publication-title: J Mech Mater Struct – volume: 48 start-page: 1 year: 2007 end-page: 20 ident: CR20 article-title: Micromechanical modeling of dynamic compressive responses of mesoscopic heterogenous brittle rock publication-title: Theor Appl Fract Mech – volume: 124 start-page: 1177 year: 1998 end-page: 1185 ident: CR71 article-title: General regression neural networks for driven piles in cohesionless soils publication-title: J Geotech Geoenviron Eng – volume: 34 start-page: 319 year: 2018 end-page: 327 ident: CR53 article-title: Prediction of bearing capacity of thin-walled foundation: a simulation approach publication-title: Eng Comput – volume: 21 start-page: 1087 year: 1953 end-page: 1092 ident: CR92 article-title: Equation of state calculations by fast computing machines publication-title: J Chem Phys – year: 2019 ident: CR76 article-title: A new development of ANFIS–GMDH optimized by PSO to predict pile bearing capacity based on experimental datasets publication-title: Eng Comput doi: 10.1007/s00366-019-00849-3 – year: 2018 ident: CR28 article-title: Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions publication-title: Soft Comput doi: 10.1007/s00500-018-3253-3 – volume: 50 start-page: 2177 year: 2018 end-page: 2191 ident: CR41 article-title: Multi-planar detection optimization algorithm for the interval charging structure of large-diameter longhole blasting design based on rock fragmentation aspects publication-title: Eng Optim – year: 2008 ident: CR81 publication-title: The engineering of foundations – volume: 13 start-page: 354 year: 2013 end-page: 369 ident: CR94 article-title: An empirical model for shear capacity of RC deep beams using genetic-simulated annealing publication-title: Arch Civ Mech Eng – volume: 220 start-page: 671 issue: 80- year: 1983 end-page: 680 ident: CR93 article-title: Optimization by simulated annealing publication-title: Science – volume: 74 start-page: 548 year: 2013 end-page: 555 ident: CR99 article-title: A novel machine learning approach for estimation of electricity demand: an empirical evidence from Thailand publication-title: Energy Convers Manag – volume: 1 start-page: 49 year: 1984 end-page: 55 ident: CR84 article-title: Wave equation analysis and dynamic monitoring publication-title: Deep Found J – volume: 63 start-page: 159 year: 2013 end-page: 169 ident: CR64 article-title: Application of genetic programming to predict the uniaxial compressive strength and elastic modulus of carbonate rocks publication-title: Int J Rock Mech Min Sci – volume: 46 start-page: 1214 year: 2013 end-page: 1222 ident: CR22 article-title: Prediction of blast-induced ground vibration using artificial neural network publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2009.03.004 – volume: 49 start-page: 1 year: 2016 end-page: 11 ident: CR25 article-title: Risk assessment and prediction of flyrock distance by combined multiple regression analysis and monte carlo simulation of quarry blasting publication-title: Rock Mech Rock Eng doi: 10.1007/s00603-016-1015-z – volume: 38 start-page: 281 year: 2011 end-page: 286 ident: CR108 article-title: Empirical modeling of plate load test moduli of soil via gene expression programming publication-title: Comput Geotech – volume: 9 start-page: 1042 year: 2019 ident: CR13 article-title: Assessing dynamic conditions of the retaining wall: developing two hybrid intelligent models publication-title: Appl Sci – volume: 26 start-page: 1146 issue: 13 year: 2018 end-page: 1153 ident: CR32 article-title: Krill herd algorithm-based neural network in structural seismic reliability evaluation publication-title: Mech Adv Mater Struct – ident: CR48 – volume: 23 start-page: 248 year: 2010 end-page: 263 ident: CR88 article-title: Nonlinear genetic-based models for prediction of flow number of asphalt mixtures publication-title: J Mater Civ Eng – volume: 46 start-page: 2109 year: 2013 end-page: 2119 ident: CR112 article-title: An evolutionary approach for modeling of shear strength of RC deep beams publication-title: Mater Struct – volume: 79 start-page: 291 issue: 1 year: 2015 end-page: 316 ident: CR29 article-title: Comparative performance of six supervised learning methods for the development of models of hard rock pillar stability prediction publication-title: Natural Hazards – year: 2019 ident: CR43 article-title: The use of new intelligent techniques in designing retaining walls publication-title: Eng Comput doi: 10.1007/s00366-018-00700-1 – volume: 17 start-page: 1344 year: 2017 ident: CR8 article-title: Feed-forward neural network prediction of the mechanical properties of sandcrete materials publication-title: Sensors – volume: 35 start-page: 33 year: 2008 end-page: 46 ident: CR52 article-title: Ultimate bearing capacity prediction of shallow foundations on cohesionless soils using neurofuzzy models publication-title: Comput Geotech – volume: 7 start-page: 94692 year: 2019 end-page: 94700 ident: CR45 article-title: Improving performance of retaining walls under dynamic conditions developing an optimized ANN based on ant colony optimization technique publication-title: IEEE Access – volume: 24 start-page: 329 year: 2019 end-page: 345 ident: CR37 article-title: Application of artificial neural networks for the prediction of the compressive strength of cement-based mortars publication-title: Comput Concr – year: 2018 ident: CR80 article-title: Application of improved ANFIS approaches to estimate bearing capacity of piles publication-title: Soft Comput doi: 10.1007/s00500-018-3517-y – year: 2017 ident: CR60 article-title: Applications of particle swarm optimization in geotechnical engineering: a comprehensive review publication-title: Geotech Geol Eng doi: 10.1007/s10706-017-0356-z – volume: 78 start-page: 981 year: 2019 end-page: 990 ident: CR17 article-title: A neuro-genetic predictive model to approximate overbreak induced by drilling and blasting operation in tunnels publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-017-1116-2 – ident: CR59 – volume: 9 start-page: 4650 year: 2019 ident: CR9 article-title: A gene expression programming model for predicting tunnel convergence publication-title: Appl Sci – volume: 34 start-page: 347 year: 2018 end-page: 356 ident: CR74 article-title: Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil publication-title: Eng Comput – volume: 124 start-page: 529 year: 2018 end-page: 538 ident: CR5 article-title: Experimental and intelligent techniques to estimate bearing capacity of cohesive soft soils reinforced with soil-cement columns publication-title: Measurement – volume: 75 start-page: 289 year: 2015 end-page: 297 ident: CR7 article-title: Feasibility of indirect determination of blast induced ground vibration based on support vector machine publication-title: Measurement – volume: 9 start-page: 1042 year: 2019 ident: 932_CR13 publication-title: Appl Sci doi: 10.3390/app9061042 – volume-title: Probability and statistics in civil engineering year: 1986 ident: 932_CR104 – volume: 2016 start-page: 20 year: 2016 ident: 932_CR10 publication-title: Comput Intell Neurosci doi: 10.1155/2016/5104907 – volume: 23 start-page: 733 year: 2013 ident: 932_CR67 publication-title: Int J Min Sci Technol doi: 10.1016/j.ijmst.2013.08.018 – volume: 19 start-page: 1041 year: 2017 ident: 932_CR105 publication-title: Int J Fuzzy Syst doi: 10.1007/s40815-017-0324-z – volume: 18 start-page: 1355 year: 2019 ident: 932_CR46 publication-title: Struct Heal Monit doi: 10.1177/1475921718797949 – volume: 46 start-page: 2109 year: 2013 ident: 932_CR112 publication-title: Mater Struct doi: 10.1617/s11527-013-0039-z – volume: 35 start-page: 33 year: 2008 ident: 932_CR52 publication-title: Comput Geotech doi: 10.1016/j.compgeo.2007.03.001 – volume: 79 start-page: 291 issue: 1 year: 2015 ident: 932_CR29 publication-title: Natural Hazards doi: 10.1007/s11069-015-1842-3 – volume: 181 start-page: 5227 year: 2011 ident: 932_CR86 publication-title: Inf Sci (Ny) doi: 10.1016/j.ins.2011.07.026 – volume: 102 start-page: 11962 year: 1976 ident: 932_CR1 publication-title: J Geotech Geoenviron Eng – volume: 23 start-page: 248 year: 2010 ident: 932_CR88 publication-title: J Mater Civ Eng doi: 10.1061/(ASCE)MT.1943-5533.0000154 – volume: 220 start-page: 671 issue: 80- year: 1983 ident: 932_CR93 publication-title: Science doi: 10.1126/science.220.4598.671 – volume: 185 start-page: 20 year: 2015 ident: 932_CR21 publication-title: Eng Geol doi: 10.1016/j.enggeo.2014.11.016 – volume: 74 start-page: 120 year: 2014 ident: 932_CR110 publication-title: Comput Ind Eng doi: 10.1016/j.cie.2014.05.010 – volume: 63 start-page: 159 year: 2013 ident: 932_CR64 publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2013.08.004 – volume: 69 start-page: 59 year: 2014 ident: 932_CR16 publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2014.03.003 – volume: 9 start-page: 243 year: 2019 ident: 932_CR36 publication-title: Appl Sci doi: 10.3390/app9020243 – volume-title: Dynamics studies on the bearing capacity of piles: final report to the Ohio Department of Highways year: 1970 ident: 932_CR83 – ident: 932_CR3 – volume: 7 start-page: 94692 year: 2019 ident: 932_CR45 publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2927632 – year: 2019 ident: 932_CR90 publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-019-01626-8 – year: 2019 ident: 932_CR30 publication-title: Nat Resour Res doi: 10.1007/s11053-019-09519-z – year: 2019 ident: 932_CR78 publication-title: Eng Comput doi: 10.1007/s00366-019-00752-x – volume: 11 start-page: 1932 year: 2011 ident: 932_CR65 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2010.06.009 – volume: 75 start-page: 739 year: 2016 ident: 932_CR26 publication-title: Environ Earth Sci doi: 10.1007/s12665-016-5524-6 – volume: 46 start-page: 1214 year: 2013 ident: 932_CR22 publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2009.03.004 – volume: 31 start-page: 409 year: 2019 ident: 932_CR33 publication-title: Neural Comput Appl doi: 10.1007/s00521-017-3007-7 – volume: 118 start-page: 505 year: 2019 ident: 932_CR31 publication-title: Saf Sci doi: 10.1016/j.ssci.2019.05.046 – volume-title: Genetic programming: on the programming of computers by means of natural selection year: 1992 ident: 932_CR56 – volume: 34 start-page: 319 year: 2018 ident: 932_CR53 publication-title: Eng Comput doi: 10.1007/s00366-017-0542-x – volume: 74 start-page: 1301 year: 2015 ident: 932_CR51 publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-014-0687-4 – volume: 33 start-page: 45 year: 2017 ident: 932_CR23 publication-title: Eng Comput doi: 10.1007/s00366-016-0455-0 – year: 2019 ident: 932_CR76 publication-title: Eng Comput doi: 10.1007/s00366-019-00849-3 – volume: 50 start-page: 2177 year: 2018 ident: 932_CR41 publication-title: Eng Optim doi: 10.1080/0305215X.2018.1439943 – volume: 8 start-page: 9647 year: 2015 ident: 932_CR54 publication-title: Arab J Geosci doi: 10.1007/s12517-015-1908-2 – year: 2016 ident: 932_CR70 publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-016-0872-8 – ident: 932_CR48 – volume: 20 start-page: s102 year: 2016 ident: 932_CR34 publication-title: Eur J Environ Civ Eng doi: 10.1080/19648189.2016.1246693 – volume: 75 start-page: 289 year: 2015 ident: 932_CR7 publication-title: Measurement doi: 10.1016/j.measurement.2015.07.019 – year: 2018 ident: 932_CR28 publication-title: Soft Comput doi: 10.1007/s00500-018-3253-3 – year: 2019 ident: 932_CR58 publication-title: Eng Comput doi: 10.1007/s00366-019-00770-9 – volume: 24 start-page: 469 year: 2019 ident: 932_CR35 publication-title: Comput Concr – volume: 35 start-page: 111 year: 2008 ident: 932_CR63 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2007.06.006 – volume: 86 start-page: 35 year: 1960 ident: 932_CR82 publication-title: J Soil Mech ASCE – ident: 932_CR59 – volume: 9 start-page: 2788 year: 2019 ident: 932_CR11 publication-title: Appl Sci doi: 10.3390/app9142788 – volume: 13 start-page: 354 year: 2013 ident: 932_CR94 publication-title: Arch Civ Mech Eng doi: 10.1016/j.acme.2013.02.007 – volume-title: The engineering of foundations year: 2008 ident: 932_CR81 – volume: 49 start-page: 1 year: 2016 ident: 932_CR25 publication-title: Rock Mech Rock Eng doi: 10.1007/s00603-016-1015-z – volume: 46 start-page: 1214 year: 2009 ident: 932_CR44 publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2009.03.004 – volume: 37 start-page: 1318 year: 2011 ident: 932_CR66 publication-title: Comput Geosci doi: 10.1016/j.cageo.2010.09.002 – volume: 48 start-page: 1 year: 2007 ident: 932_CR20 publication-title: Theor Appl Fract Mech doi: 10.1016/j.tafmec.2007.04.008 – volume: 24 start-page: 329 year: 2019 ident: 932_CR37 publication-title: Comput Concr – volume: 26 start-page: 1146 issue: 13 year: 2018 ident: 932_CR32 publication-title: Mech Adv Mater Struct doi: 10.1080/15376494.2018.1430874 – volume: 50 start-page: 629 issue: 4 year: 2012 ident: 932_CR27 publication-title: Safe Sci doi: 10.1016/j.ssci.2011.08.065 – volume: 122 start-page: 492 year: 1996 ident: 932_CR49 publication-title: J Geotech Eng doi: 10.1061/(ASCE)0733-9410(1996)122:6(492) – volume: 122 start-page: 50 year: 2018 ident: 932_CR101 publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2018.04.004 – volume: 36 start-page: 1434 year: 2012 ident: 932_CR77 publication-title: Int J Numer Anal Methods Geomech doi: 10.1002/nag.1076 – volume: 551 start-page: 504 year: 2005 ident: 932_CR85 publication-title: Nucl Instruments Methods Phys Res Sect A Accel Spectrometers Detect Assoc Equip doi: 10.1016/j.nima.2005.05.069 – volume-title: Axial bearing capacity of piles and modelling of distribution of skin resistance with depth year: 2012 ident: 932_CR2 – volume: 74 start-page: 548 year: 2013 ident: 932_CR99 publication-title: Energy Convers Manag doi: 10.1016/j.enconman.2013.06.031 – volume: 57 start-page: 122 year: 2014 ident: 932_CR73 publication-title: Measurement doi: 10.1016/j.measurement.2014.08.007 – year: 2019 ident: 932_CR47 publication-title: Measurement doi: 10.1016/j.measurement.2019.06.007 – volume: 81 start-page: 112 year: 2018 ident: 932_CR19 publication-title: Tunn Undergr Sp Technol doi: 10.1016/j.tust.2018.07.023 – volume: 74 start-page: 2845 year: 2015 ident: 932_CR55 publication-title: Environ Earth Sci doi: 10.1007/s12665-015-4305-y – volume: 33 start-page: 4019024 year: 2019 ident: 932_CR40 publication-title: J Perform Constr Facil doi: 10.1061/(ASCE)CF.1943-5509.0001292 – volume: 78 start-page: 981 year: 2019 ident: 932_CR17 publication-title: Bull Eng Geol Environ doi: 10.1007/s10064-017-1116-2 – volume: 44 start-page: 954 year: 2007 ident: 932_CR62 publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2007.02.003 – volume: 38 start-page: 5352 year: 2011 ident: 932_CR96 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2010.10.021 – year: 2017 ident: 932_CR60 publication-title: Geotech Geol Eng doi: 10.1007/s10706-017-0356-z – volume: 80 start-page: 841 year: 2010 ident: 932_CR98 publication-title: Text Res J doi: 10.1177/0040517509355344 – volume: 27 start-page: 302 year: 2008 ident: 932_CR109 publication-title: QSAR Comb Sci doi: 10.1002/qsar.200710043 – volume-title: Handbook of genetic programming applications year: 2015 ident: 932_CR91 doi: 10.1007/978-3-319-20883-1 – volume: 34 start-page: 347 year: 2018 ident: 932_CR74 publication-title: Eng Comput doi: 10.1007/s00366-017-0545-7 – volume: 36 start-page: 2057 year: 2018 ident: 932_CR79 publication-title: Geotech Geol Eng doi: 10.1007/s10706-018-0445-7 – volume: 17 start-page: 609 year: 2017 ident: 932_CR102 publication-title: Arch Civ Mech Eng doi: 10.1016/j.acme.2016.11.005 – volume: 9 start-page: 4650 year: 2019 ident: 932_CR9 publication-title: Appl Sci doi: 10.3390/app9214650 – year: 2019 ident: 932_CR43 publication-title: Eng Comput doi: 10.1007/s00366-018-00700-1 – start-page: 26 volume-title: International foundation congress and equipment expo (IFCEE’09) year: 2009 ident: 932_CR72 – volume: 17 start-page: 924 year: 2019 ident: 932_CR15 publication-title: Procedia Struct Integr doi: 10.1016/j.prostr.2019.08.123 – volume: 30 start-page: 457 year: 2019 ident: 932_CR4 publication-title: Steel Compos Struct – volume: 30 start-page: 4016003 year: 2016 ident: 932_CR42 publication-title: J Comput Civ Eng doi: 10.1061/(ASCE)CP.1943-5487.0000553 – volume: 23 start-page: 665 year: 1993 ident: 932_CR95 publication-title: IEEE Trans Syst Man Cybern doi: 10.1109/21.256541 – volume: 28 start-page: 439 year: 2018 ident: 932_CR24 publication-title: Steel Compos Struct – volume: 28 start-page: 242 year: 2011 ident: 932_CR100 publication-title: Eng Comput doi: 10.1108/02644401111118132 – volume: 38 start-page: 281 year: 2011 ident: 932_CR108 publication-title: Comput Geotech doi: 10.1016/j.compgeo.2010.11.008 – volume: 124 start-page: 529 year: 2018 ident: 932_CR5 publication-title: Measurement doi: 10.1016/j.measurement.2018.04.057 – volume: 1 start-page: 49 year: 1984 ident: 932_CR84 publication-title: Deep Found J – volume: 124 start-page: 1177 year: 1998 ident: 932_CR71 publication-title: J Geotech Geoenviron Eng doi: 10.1061/(ASCE)1090-0241(1998)124:12(1177) – volume: 20 start-page: 269 year: 2002 ident: 932_CR107 publication-title: J Mol Graph Model doi: 10.1016/S1093-3263(01)00123-1 – volume: 29 start-page: 619 year: 2018 ident: 932_CR39 publication-title: Neural Comput Appl doi: 10.1007/s00521-016-2598-8 – volume: 239 start-page: 119 year: 2018 ident: 932_CR18 publication-title: Eng Geol doi: 10.1016/j.enggeo.2018.03.023 – volume: 9 start-page: 3715 year: 2019 ident: 932_CR14 publication-title: Appl Sci doi: 10.3390/app9183715 – ident: 932_CR87 doi: 10.1007/978-1-84628-663-6_3 – year: 2017 ident: 932_CR57 publication-title: Geotech Geol Eng doi: 10.1007/s10706-017-0254-4 – year: 2016 ident: 932_CR68 publication-title: Eng Comput doi: 10.1007/s00366-015-0404-3 – volume: 63 start-page: 29 year: 2017 ident: 932_CR111 publication-title: Tunn Undergr Sp Technol doi: 10.1016/j.tust.2016.12.009 – volume: 28 start-page: 499 year: 2017 ident: 932_CR106 publication-title: Neural Comput Appl doi: 10.1007/s00521-015-2078-6 – volume: 17 start-page: 1344 year: 2017 ident: 932_CR8 publication-title: Sensors doi: 10.3390/s17061344 – volume: 17 start-page: 914 year: 2019 ident: 932_CR12 publication-title: Procedia Struct Integr doi: 10.1016/j.prostr.2019.08.122 – volume: 21 start-page: 1087 year: 1953 ident: 932_CR92 publication-title: J Chem Phys doi: 10.1063/1.1699114 – volume: 81 start-page: 632 year: 2018 ident: 932_CR38 publication-title: Tunn Undergr Sp Technol doi: 10.1016/j.tust.2018.08.029 – volume: 529 start-page: 1590 year: 2015 ident: 932_CR61 publication-title: J Hydrol doi: 10.1016/j.jhydrol.2015.08.025 – volume: 146 start-page: 110 year: 2019 ident: 932_CR6 publication-title: Measurement doi: 10.1016/j.measurement.2019.04.081 – year: 2018 ident: 932_CR80 publication-title: Soft Comput doi: 10.1007/s00500-018-3517-y – volume: 28 start-page: 391 year: 2017 ident: 932_CR75 publication-title: Neural Comput Appl doi: 10.1007/s00521-015-2072-z – volume: 27 start-page: 707 year: 2016 ident: 932_CR103 publication-title: Neural Comput Appl doi: 10.1007/s00521-015-1890-3 – volume: 88 start-page: 254 year: 2016 ident: 932_CR69 publication-title: Int J Rock Mech Min Sci doi: 10.1016/j.ijrmms.2016.07.028 – volume: 36 start-page: 7809 year: 2009 ident: 932_CR97 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2008.11.019 – volume: 134 start-page: 1021 year: 2008 ident: 932_CR50 publication-title: J Geotech Geoenviron Eng doi: 10.1061/(ASCE)1090-0241(2008)134:7(1021) – volume: 5 start-page: 735 year: 2010 ident: 932_CR89 publication-title: J Mech Mater Struct doi: 10.2140/jomms.2010.5.735
SSID	ssj0013009
Score	2.5083134
Snippet	The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP)...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	2111
SubjectTerms	Area CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer-Aided Engineering (CAD Control Cross-sections Driven piles Drop hammers Estimation Fuzzy logic Genetic algorithms Machine learning Math. Applications in Chemistry Mathematical and Computational Engineering Original Article Performance indices Pile bearing capacities Prediction models Predictions Sensitivity analysis Simulated annealing Systems Theory
SummonAdditionalLinks	– databaseName: ProQuest Central dbid: BENPR link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NT8IwFH9R8KAHUdSIX-nBmzayUrb2ZNRAPBFiNPG2dF0XSRSQTRL_e98bBdRELp7bNUve1-_Xvg-Ac2u1DKSTHLE2EhQhFDcuaHNjTCuUiRTWJOWwiajXU8_Puu8v3HKfVjn3iaWjTkeW7sivkMgoTXgmvB6_c5oaRa-rfoTGOlSpUxnqefW20-s_LN8RmrMkjyCiJK8w8mUzZfEctWIhNq050XrB9c_QtMSbv55Iy8jTrf33n3dg22NOdjNTkl1Yc8M61Dz-ZN668zpsfWtOuAfTG4aQm718Uk0XywdvNOgL9xv0zIaK2DlFwJShBlIhJPOZXm-4whadYVkxwgV6DCoYQk1G6YuIkR1L0MJop8VgbZEJsFHGxuih8n146nYe7-65n9LALZpvwXXTBlGmlJVGo2itCRNpsySLqEa3rdLAqSzBEIg8PNNNZYNUpjpKJRIVFWrk8gdQGY6G7hBYSwQ2cy5zyNGkMBhGVLNl2sIJhboThg0I5gKKrW9hTpM0XuNF8-VSqDEKNS6FGusGXCy-Gc8aeKzcfTKXZOyNOY-XYmzA5VwXlst_n3a0-rRj2BSUIVMm_55ApZh8uFPYsNNikE_OvCp_AaDI-qE priority: 102 providerName: ProQuest
Title	A new hybrid simulated annealing-based genetic programming technique to predict the ultimate bearing capacity of piles
URI	https://link.springer.com/article/10.1007/s00366-019-00932-9 https://www.proquest.com/docview/2548900996
Volume	37
WOSCitedRecordID	wos000574106600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAVX databaseName: Springer LINK customDbUrl: eissn: 1435-5663 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0013009 issn: 0177-0667 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1RT9swED4B5WF7WKEMwWCVH3hjlhrXSexHQFSTJlXVOhDiJXIcR1SCtmoyJP5Nf0t_GXep0zLEkLaXPNiOZdln33267-4ATqzVMpBOcrS1EaAIobhxQciNMd1IplJYk1bFJuJ-X93c6IEPCitqtnvtkqxe6lWwG6VOIfSrOcFwwfUmNELKNkMYfXi99h10lsSOICZiVxT7UJm35_hTHa1tzFdu0Urb9Jr_t84d-OStS3a2FIdd2HDjFjS9pcn8PS6wqS7mULe14OOLzIR78HTG0N5md08U0LWYF6MHKvOFcxh8lw2FsHPSfxlD-aMwyMXcE70esIutEsOycsKmM_IFlQwtTUbsRTSR3WKe4g2joRaVtUUkwCY5m-ILVXyGq97lr4vv3Fdp4Bavb8l1xwZxrpSVRuPRWhOl0uZpHlOMbqiywKk8RRWIODzXHWWDTGY6ziQCFRVpxPL7sDWejN0BsK4IbO5c7hCjSWFQjahO14TCCYWyE0WHENSHlVifwpwqadwnq-TL1eYnuPlJtfmJPoTT1T_TZQKPd0cf1zKQ-MtcJIihlSZTGhfwrT7zdfffZ_vyb8OP4IMgxkxFBj6GrXL2232FbftYjopZGxrnl_3BzzZs_oh5mziqQ_wOwtt2Jf7PurD9tA
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3JTsMwEB2xScCBHVFWH-AEFo3rJvYBIcQiUKHiABK34DiOqARtIQHET_GNzKRJC0hw48DZjhU5b5aX2QA2rdXSk05y9LWRoAihuHFenRtjar6MpLAmyodNBM2murnRl0PwXtbCUFplqRNzRR13LP0j30UiozT5M_5-95HT1CiKrpYjNHqwaLi3V6Rs6d7ZEX7fLSFOjq8OT3kxVYBbhFvGddV6QaKUlUbjq1jjR9ImURJQTWldxZ5TSYQqG3ljoqvKerGMdRBLdKyVr5F74rnDMCpryieJagR8ELWo9lJKvIBSyvygKNLJS_Wo8Qtxd83pJ4Lg-qshHHi33wKyuZ07mf5vNzQDU4VHzQ56IjALQ649B9OFd80K3ZXOweSn1ovz8HLAkFCwuzeqWGNp64HGmOF-g3bHUIk-J_seM5QvKvNkRR7bA66wft9blnVwgUJdGUNHmlFyJjIAxyK8Btpp0RWxyHNYJ2Fd1L_pAlz_yV0swki703ZLwGrCs4lziUMGKoVBI6mqNVMXTiiUDN-vgFcCIrRFg3aaE3If9ltL5yAKEURhDqJQV2C7_0y3157k192rJXLCQlWl4QA2FdgpsTdY_vm05d9P24Dx06uL8_D8rNlYgQlBuUB5mvMqjGRPz24NxuxL1kqf1nMhYnD715j8ADDDVbc
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3Nb9MwFH8aHULjQGEfolvZfGAnsNa4bmIfJlTYqk1FVYVA2i1zHFtMYm1Zwqb9a_x1vJc6LUxitx12tmNFzu99_PK-AN5aq2UkneToayNBEUJx46IeN8Z0Y5lJYU1WDZtIRiN1dqbHK_C7roWhtMpaJ1aKOp9a-kd-gERGafJn4gMf0iLGR4MPs5-cJkhRpLUepzGHyNDd3iB9Kw5Pj_Bb7wsxOP766YSHCQPcIvRKrjs2SrxSVhqNr2VNnEnrM59QfWlP5ZFTPkP1jRzS646yUS5zneQSnWwVa-SheO4TWE26SHoasPrxeDT-soxhdOYJJlFCCWZxEkp2qsI9agNDTF5z-qUguP7XLC593Tvh2crqDZqP-b5ewovga7P-XDhewYqbrEMz-N0saLViHZ7_1ZRxA677DKkG-35LtWysuLikAWe436BFMlS8z8ny5wwljwpAWchwu8QVtuiIy8opLlAQrGToYjNK20Ru4FiG10A7LTopFhkQm3o2Q81cbMK3B7mLLWhMphP3GlhXRNY75x1yUykMmk_V6ZqecEKhzMRxC6IaHKkNrdtpgsiPdNF0ugJUioBKK0ClugXvFs_M5o1L7t3drlGUBiVWpEsIteB9jcPl8v9P277_tD14hlBMP5-OhjuwJihJqMp_bkOjvPrl3sBTe11eFFe7QaIYnD80KP8AHL9gCQ
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+new+hybrid%C2%A0simulated+annealing-based+genetic%C2%A0programming+technique+to+predict+the+ultimate%C2%A0bearing+capacity+of+piles&rft.jtitle=Engineering+with+computers&rft.au=Yong%2C+Weixun&rft.au=Zhou%2C+Jian&rft.au=Jahed+Armaghani%2C+Danial&rft.au=Tahir%2C+M.+M.&rft.date=2021-07-01&rft.pub=Springer+London&rft.issn=0177-0667&rft.eissn=1435-5663&rft.volume=37&rft.issue=3&rft.spage=2111&rft.epage=2127&rft_id=info:doi/10.1007%2Fs00366-019-00932-9&rft.externalDocID=10_1007_s00366_019_00932_9
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0177-0667&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0177-0667&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0177-0667&client=summon