Global chaotic bat algorithm for feature selection

The wrapper algorithm adopts the performance of the learning algorithm as the evaluation criteria to obtain excellent classification performance. However, the wrapper algorithm is prone to converge prematurely. A global chaotic bat algorithm (GCBA) is put up forward to improve this shortage. First,...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	The Journal of supercomputing Jg. 78; H. 17; S. 18754 - 18776
Hauptverfasser:	Li, Ying, Cui, Xueting, Fan, Jiahao, Wang, Tan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.11.2022 Springer Nature B.V
Schlagworte:	Adaptive learning Algorithms Classification Compilers Computer Science Datasets Gene expression Interpreters Machine learning Processor Architectures Programming Languages Solution space Transfer functions Wrapper feature selection algorithm Feature selection Bat algorithm Chaotic map Classification
ISSN:	0920-8542, 1573-0484
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	The wrapper algorithm adopts the performance of the learning algorithm as the evaluation criteria to obtain excellent classification performance. However, the wrapper algorithm is prone to converge prematurely. A global chaotic bat algorithm (GCBA) is put up forward to improve this shortage. First, GCBA applies chaotic map to population initialization to cover the entire solution space. In addition, adaptive learning factors are presented to balance exploration and exploration. The learning factor of local optimal position gradually decreases in the early stage while the learning factor of global optimal position gradually increases in the later stage. Finally, to improve the exploitation, an improved transfer function is proposed, which transfers the continuous space to discrete binary space. GCBA is tested on 14 UCI data sets and 5 gene expression data sets compared with other 6 comparison algorithms. Compared with other algorithms, the results show that GCBA is able to achieve better classification performance.
AbstractList	The wrapper algorithm adopts the performance of the learning algorithm as the evaluation criteria to obtain excellent classification performance. However, the wrapper algorithm is prone to converge prematurely. A global chaotic bat algorithm (GCBA) is put up forward to improve this shortage. First, GCBA applies chaotic map to population initialization to cover the entire solution space. In addition, adaptive learning factors are presented to balance exploration and exploration. The learning factor of local optimal position gradually decreases in the early stage while the learning factor of global optimal position gradually increases in the later stage. Finally, to improve the exploitation, an improved transfer function is proposed, which transfers the continuous space to discrete binary space. GCBA is tested on 14 UCI data sets and 5 gene expression data sets compared with other 6 comparison algorithms. Compared with other algorithms, the results show that GCBA is able to achieve better classification performance. The wrapper algorithm adopts the performance of the learning algorithm as the evaluation criteria to obtain excellent classification performance. However, the wrapper algorithm is prone to converge prematurely. A global chaotic bat algorithm (GCBA) is put up forward to improve this shortage. First, GCBA applies chaotic map to population initialization to cover the entire solution space. In addition, adaptive learning factors are presented to balance exploration and exploration. The learning factor of local optimal position gradually decreases in the early stage while the learning factor of global optimal position gradually increases in the later stage. Finally, to improve the exploitation, an improved transfer function is proposed, which transfers the continuous space to discrete binary space. GCBA is tested on 14 UCI data sets and 5 gene expression data sets compared with other 6 comparison algorithms. Compared with other algorithms, the results show that GCBA is able to achieve better classification performance.
Author	Fan, Jiahao Wang, Tan Li, Ying Cui, Xueting
Author_xml	– sequence: 1 givenname: Ying surname: Li fullname: Li, Ying organization: College of Computer Science and Technology, Jilin University, Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University – sequence: 2 givenname: Xueting surname: Cui fullname: Cui, Xueting organization: College of Computer Science and Technology, Jilin University, Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University – sequence: 3 givenname: Jiahao orcidid: 0000-0002-0818-8533 surname: Fan fullname: Fan, Jiahao email: jihanfan@hotmail.com organization: College of Computer Science and Technology, Jilin University, Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University – sequence: 4 givenname: Tan surname: Wang fullname: Wang, Tan organization: Northeast Asian Research Center, Jilin University
BookMark	eNp9kMFOwzAMhiM0JLbBC3CqxLngOG3SHNEEA2kSFzhHbpZunbpmJNmBt6ejSEgcdrIs-fNvfzM26X3vGLvlcM8B1EPkHFHlgJhDIUHmcMGmvFRiaKtiwqagEfKqLPCKzWLcAUAhlJgyXHa-pi6zW_KptVlNKaNu40Obtvus8SFrHKVjcFl0nbOp9f01u2yoi-7mt87Zx_PT--IlX70tXxePq9wKrlOuC67rUpHitVQlIYB0hbNcaHK2ULrRZKVC4FaDJIkNCtvwcm0tibXmJObsbtx7CP7z6GIyO38M_RBpUKEuS62xGqZwnLLBxxhcYw6h3VP4MhzMyY0Z3ZjBjflxY2CAqn-QbROdnkuB2u48KkY0Djn9xoW_q85Q309xeTI
CitedBy_id	crossref_primary_10_1007_s11227_023_05865_1 crossref_primary_10_1016_j_matcom_2023_12_037 crossref_primary_10_1007_s00521_024_10837_4 crossref_primary_10_1007_s00500_024_09876_9 crossref_primary_10_1007_s13042_025_02588_y crossref_primary_10_1109_ACCESS_2024_3367440
Cites_doi	10.1016/j.asoc.2012.03.068 10.1016/j.ejor.2016.07.012 10.1016/j.neucom.2021.03.077 10.1007/s10898-016-0461-1 10.1016/j.ejor.2014.10.062 10.1016/j.jocs.2013.10.002 10.1016/j.compstruc.2012.09.003 10.3390/computation7030049 10.1016/j.eswa.2020.113377 10.1016/j.eswa.2018.04.024 10.1109/INTELCIS.2017.8260031 10.1007/s11227-021-03773-w 10.1007/s00521-020-05055-7 10.1504/IJDMB.2017.088538 10.1016/j.ins.2009.03.004 10.1016/j.knosys.2021.106894 10.1051/matecconf/20167801118 10.1155/2014/630280 10.1016/j.eswa.2017.04.019 10.1016/j.future.2020.06.031 10.1016/j.neucom.2021.03.061 10.1155/2017/4367342 10.1007/s00521-013-1525-5 10.1007/s10489-020-01898-8 10.1016/j.asoc.2014.11.029 10.1007/s11227-018-2625-x 10.1016/j.eswa.2012.03.066 10.1016/j.asoc.2018.06.034 10.1016/j.neucom.2014.06.067 10.1109/TEVC.2020.2968743 10.1016/j.ins.2006.09.012 10.1016/j.asoc.2021.107372 10.1016/j.neucom.2017.07.039 10.1007/s10462-012-9328-0 10.1007/s10489-018-1158-6 10.1007/978-3-540-78987-1_21 10.1016/j.ins.2017.08.047 10.1007/s00521-015-2103-9 10.1016/j.future.2019.07.015 10.1016/j.eswa.2019.06.044 10.1007/978-981-10-4600-1_7 10.1371/journal.pone.0260725 10.1016/j.protcy.2012.05.131 10.1109/IranianCIS.2014.6802527 10.1016/j.swevo.2015.05.003 10.1016/j.ins.2019.08.040 10.1016/j.ins.2016.03.051
ContentType	Journal Article
Copyright	The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.
DBID	AAYXX CITATION JQ2
DOI	10.1007/s11227-022-04606-0
DatabaseName	CrossRef ProQuest Computer Science Collection
DatabaseTitle	CrossRef ProQuest Computer Science Collection
DatabaseTitleList	ProQuest Computer Science Collection
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1573-0484
EndPage	18776
ExternalDocumentID	10_1007_s11227_022_04606_0
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C .4S .86 .DC .VR 06D 0R~ 0VY 123 199 1N0 1SB 2.D 203 28- 29L 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 4.4 406 408 409 40D 40E 5QI 5VS 67Z 6NX 78A 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYOK AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDBF ABDPE ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACUHS ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADMLS ADQRH ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHSBF AHYZX AI. AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN B-. B0M BA0 BBWZM BDATZ BGNMA BSONS CAG COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 EAD EAP EAS EBD EBLON EBS EDO EIOEI EJD EMK EPL ESBYG ESX F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GXS H13 HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ H~9 I-F I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KOW LAK LLZTM M4Y MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P2P P9O PF0 PT4 PT5 QOK QOS R4E R89 R9I RHV RNI ROL RPX RSV RZC RZE 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 TEORI TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW VH1 W23 W48 WH7 WK8 YLTOR Z45 Z7R Z7X Z7Z Z83 Z88 Z8M Z8N Z8R Z8T Z8W Z92 ZMTXR ~8M ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABJCF ABRTQ ACSTC ADHKG ADKFA AEZWR AFDZB AFFHD AFHIU AFKRA AFOHR AGQPQ AHPBZ AHWEU AIXLP ARAPS ATHPR AYFIA BENPR BGLVJ CCPQU CITATION HCIFZ K7- M7S PHGZM PHGZT PQGLB PTHSS JQ2
ID	FETCH-LOGICAL-c319t-9419b57a71b675a2006e4ec139aec479f9ac67201c906a62f23cf15dcca3d91a3
IEDL.DBID	RSV
ISICitedReferencesCount	4
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000810326200004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0920-8542
IngestDate	Sat Nov 01 15:16:30 EDT 2025 Tue Nov 18 21:55:06 EST 2025 Sat Nov 29 04:27:42 EST 2025 Fri Feb 21 02:47:26 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	17
Keywords	Wrapper feature selection algorithm Feature selection Bat algorithm Chaotic map Classification
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c319t-9419b57a71b675a2006e4ec139aec479f9ac67201c906a62f23cf15dcca3d91a3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-0818-8533
PQID	2729559928
PQPubID	2043774
PageCount	23
ParticipantIDs	proquest_journals_2729559928 crossref_primary_10_1007_s11227_022_04606_0 crossref_citationtrail_10_1007_s11227_022_04606_0 springer_journals_10_1007_s11227_022_04606_0
PublicationCentury	2000
PublicationDate	2022-11-01
PublicationDateYYYYMMDD	2022-11-01
PublicationDate_xml	– month: 11 year: 2022 text: 2022-11-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationSubtitle	An International Journal of High-Performance Computer Design, Analysis, and Use
PublicationTitle	The Journal of supercomputing
PublicationTitleAbbrev	J Supercomput
PublicationYear	2022
Publisher	Springer US Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer Nature B.V
References	Mohapatra, Chakravarty, Dash (CR22) 2015; 24 Kilic, Kaya, Yildirim (CR50) 2021; 219 Karaboga, Gorkemli, Ozturk, Karaboga (CR24) 2014; 42 CR38 Dubois-Lacoste, Lopez-Ibanez, Stutzle (CR3) 2015; 243 CR33 CR31 Shareh, Bargh, Hosseinabadi, Slowik (CR29) 2021; 33 CR30 Sayed, Khoriba, Haggag (CR45) 2018; 48 Kaveh, Khayatazad (CR18) 2012; 112 Zhang, Song, Gong (CR12) 2017; 418 Wang, Liu, Xiang (CR7) 2017; 2017 Zhang, Cheng, Shi (CR11) 2019; 137 Yang (CR25) 2010; 284 CR49 Zhou, Chen, Cao, Chu, Lu (CR35) 2021; 449 Cui, Li, Fan (CR43) 2020; 41 CR46 Rashedi, Nezamabadi-Pour, Saryazdi (CR16) 2009; 179 Ahmad, Tajudin, Al-Betar, Mohammad (CR32) 2017; 19 Faramarzi, Heidarinejad, Mirjalili, Gandomi (CR1) 2020; 152 Fan, Li, Wang (CR44) 2021; 16 Gu, Budati (CR28) 2020; 113 Murugan, Mohan, Rajan, Sundari, Arunachalam (CR39) 2018; 72 Song, Zhang, Guo (CR9) 2020; 24 Agarwal, Bharti (CR5) 2021; 4 Hashim, Houssein, Mabrouk (CR13) 2019; 101 Abdechiri, Meybodi, Bahrami (CR15) 2013; 13 Zhang, Gong, Gao (CR10) 2020; 507 CR14 Kashef, Nezamabadi-Pour (CR20) 2015; 147 Luo, Zhou, Xie, Ma, Li (CR37) 2014; 2014 Montiel, Castillo, Melin (CR8) 2007; 177 Li, Mao, Lin, Zhang (CR19) 2021; 447 Al-Roomi, El-Hawary (CR6) 2016; 360 Gerber, Bornn (CR4) 2017; 68 Alatas (CR17) 2012; 39 Mirjalili, Mirjalili, Yang (CR26) 2014; 25 Saleem, Zafar, Sabzwari (CR48) 2019; 7 Alsalibi, Abualigah, Khader (CR42) 2021; 51 Chen, Xu, Wang, Zheng, Xu, Fan, Cui (CR21) 2017; 83 Al-Betar, Awadallah (CR40) 2018; 107 Yilmaz, Kucuksille (CR27) 2015; 28 Gandomi, Yang (CR36) 2014; 5 CR23 Burke, Bykov (CR2) 2016; 258 Al-Betar, Awadallah, Faris, Yang, Khader, Alomari (CR34) 2018; 273 Alickovic, Subasi (CR47) 2017; 28 Shehab, Khader, Laouched, Alomari (CR41) 2019; 75 YP Chen (4606_CR21) 2017; 83 M Shehab (4606_CR41) 2019; 75 XF Song (4606_CR9) 2020; 24 EK Burke (4606_CR2) 2016; 258 L Zhou (4606_CR35) 2021; 449 QF Luo (4606_CR37) 2014; 2014 S Kashef (4606_CR20) 2015; 147 FA Hashim (4606_CR13) 2019; 101 XT Cui (4606_CR43) 2020; 41 AR Al-Roomi (4606_CR6) 2016; 360 4606_CR46 4606_CR49 D Karaboga (4606_CR24) 2014; 42 S Yilmaz (4606_CR27) 2015; 28 O Montiel (4606_CR8) 2007; 177 S Mirjalili (4606_CR26) 2014; 25 MB Shareh (4606_CR29) 2021; 33 A Faramarzi (4606_CR1) 2020; 152 MA Al-Betar (4606_CR34) 2018; 273 A Kaveh (4606_CR18) 2012; 112 4606_CR14 XS Yang (4606_CR25) 2010; 284 E Rashedi (4606_CR16) 2009; 179 Y Gu (4606_CR28) 2020; 113 M Gerber (4606_CR4) 2017; 68 Y Zhang (4606_CR11) 2019; 137 B Alsalibi (4606_CR42) 2021; 51 X Li (4606_CR19) 2021; 447 4606_CR23 J Dubois-Lacoste (4606_CR3) 2015; 243 YH Wang (4606_CR7) 2017; 2017 Y Zhang (4606_CR12) 2017; 418 D Agarwal (4606_CR5) 2021; 4 M Abdechiri (4606_CR15) 2013; 13 R Murugan (4606_CR39) 2018; 72 N Saleem (4606_CR48) 2019; 7 Y Zhang (4606_CR10) 2020; 507 AO Ahmad (4606_CR32) 2017; 19 GI Sayed (4606_CR45) 2018; 48 F Kilic (4606_CR50) 2021; 219 E Alickovic (4606_CR47) 2017; 28 AH Gandomi (4606_CR36) 2014; 5 4606_CR30 JH Fan (4606_CR44) 2021; 16 4606_CR31 4606_CR33 MA Al-Betar (4606_CR40) 2018; 107 4606_CR38 P Mohapatra (4606_CR22) 2015; 24 B Alatas (4606_CR17) 2012; 39
References_xml	– volume: 42 start-page: 21 issue: 1 year: 2014 end-page: 57 ident: CR24 article-title: A comprehensive survey: artificial bee colony (ABC) algorithm and applications publication-title: Artif Intell Rev – volume: 41 start-page: 488 issue: 4 year: 2020 end-page: 491 ident: CR43 article-title: Global chaotic bat optimization algorithm publication-title: J Northeast Univ – volume: 39 start-page: 11080 issue: 12 year: 2012 end-page: 11088 ident: CR17 article-title: A novel chemistry based metaheuristic optimization method for mining of classification rules publication-title: Expert Syst Appl – volume: 68 start-page: 189 issue: 1 year: 2017 end-page: 217 ident: CR4 article-title: Improving simulated annealing through derandomization publication-title: J Global Optim – ident: CR49 – volume: 152 start-page: 113377 year: 2020 ident: CR1 article-title: Marine predators algorithm: a nature-inspired metaheuristic publication-title: Expert Syst Appl – volume: 5 start-page: 224 issue: 2 year: 2014 end-page: 232 ident: CR36 article-title: Chaotic bat algorithm publication-title: J Comput Sci – volume: 25 start-page: 663 issue: 3–4 year: 2014 end-page: 681 ident: CR26 article-title: Binary bat algorithm publication-title: Neural Comput Appl – volume: 72 start-page: 189 year: 2018 end-page: 217 ident: CR39 article-title: Hybridizing bat algorithm with artificial bee colony for combined heat and power economic dispatch publication-title: Appl Soft Comput – volume: 258 start-page: 70 issue: 1 year: 2016 end-page: 78 ident: CR2 article-title: The late acceptance hill-climbing heuristic publication-title: Eur J Oper Res – ident: CR46 – volume: 147 start-page: 271 year: 2015 end-page: 279 ident: CR20 article-title: An advanced ACO algorithm for feature subset selection publication-title: Neurocomputing – volume: 112 start-page: 283 year: 2012 end-page: 294 ident: CR18 article-title: A new meta-heuristic method: ray optimization publication-title: Comput Struct – volume: 418 start-page: 561 year: 2017 end-page: 574 ident: CR12 article-title: A return-cost-based binary firefly algorithm for feature selection publication-title: Inf Sci – volume: 113 start-page: 106 issue: 9 year: 2020 end-page: 112 ident: CR28 article-title: Energy-aware workflow scheduling and optimization in clouds using bat algorithm publication-title: Futur Gener Comp Syst – volume: 24 start-page: 25 year: 2015 end-page: 49 ident: CR22 article-title: An improved cuckoo search based extreme learning machine for medical data classification publication-title: Swarm Evol Comput – volume: 177 start-page: 2075 issue: 10 year: 2007 end-page: 2098 ident: CR8 article-title: Human evolutionary model: a new approach to optimization publication-title: Inf Sci – volume: 101 start-page: 646 year: 2019 end-page: 667 ident: CR13 article-title: Henry gas solubility optimization: a novel physics-based algorithm publication-title: Futur Gener Comp Syst – volume: 449 start-page: 176 year: 2021 end-page: 188 ident: CR35 article-title: Macro-micro mutual learning inside compositional model for human pose estimation publication-title: Neurocomputing – volume: 243 start-page: 369 issue: 2 year: 2015 end-page: 385 ident: CR3 article-title: Anytime Pareto local search publication-title: Eur J Oper Res – volume: 137 start-page: 46 year: 2019 end-page: 58 ident: CR11 article-title: Cost-sensitive feature selection using two-archive multi-objective artificial bee colony algorithm publication-title: Expert Syst Appl – volume: 507 start-page: 67 year: 2020 end-page: 85 ident: CR10 article-title: Binary differential evolution with self-learning for multi-objective feature selection publication-title: Inf Sci – volume: 48 start-page: 3462 issue: 10 year: 2018 end-page: 3481 ident: CR45 article-title: A novel chaotic salp swarm algorithm for global optimization and feature selection publication-title: Appl Intell – volume: 24 start-page: 882 issue: 5 year: 2020 end-page: 895 ident: CR9 article-title: Variable-size cooperative coevolutionary particle swarm optimization for feature selection on high-dimensional data publication-title: IEEE Trans Evol Comput – volume: 51 start-page: 1992 issue: 4 year: 2021 end-page: 2007 ident: CR42 article-title: A novel bat algorithm with dynamic membrane structure for optimization problems publication-title: Appl Intell – volume: 273 start-page: 448 year: 2018 end-page: 465 ident: CR34 article-title: Bat-inspired algorithms with natural selection mechanisms for global optimization publication-title: Neurocomputing – volume: 447 start-page: 64 year: 2021 end-page: 79 ident: CR19 article-title: Particle swarm optimization with state-based adaptive velocity limit strategy publication-title: Neurocomputing – ident: CR14 – ident: CR30 – volume: 107 start-page: 126 year: 2018 end-page: 145 ident: CR40 article-title: Island bat algorithm for optimization publication-title: Expert Syst Appl – volume: 16 start-page: e0260725 issue: 11 year: 2021 ident: CR44 article-title: An improved African vultures optimization algorithm based on tent chaotic mapping and time-varying mechanism publication-title: PLoS ONE – ident: CR33 – volume: 28 start-page: 753 issue: 4 year: 2017 end-page: 763 ident: CR47 article-title: Breast cancer diagnosis using GA feature selection and rotation forest publication-title: Neural Comput Appl – volume: 7 start-page: 49 issue: 3 year: 2019 ident: CR48 article-title: Enhanced feature subset selection using niche based bat algorithm publication-title: Computation – volume: 13 start-page: 2932 issue: 5 year: 2013 end-page: 2946 ident: CR15 article-title: Gases brownian motion optimization: an algorithm for optimization (GBMO) publication-title: Appl Soft Comput – ident: CR23 – volume: 28 start-page: 259 year: 2015 end-page: 275 ident: CR27 article-title: A new modification approach on bat algorithm for solving optimization problems publication-title: Appl Soft Comput – volume: 19 start-page: 32 issue: 1 year: 2017 end-page: 51 ident: CR32 article-title: Gene selection for cancer classification by combining minimum redundancy maximum relevancy and bat-inspired algorithm publication-title: Int J Data Min Bioinform – volume: 360 start-page: 73 year: 2016 end-page: 95 ident: CR6 article-title: Metropolis biogeography-based optimization publication-title: Inf Sci – volume: 2014 start-page: 630280 year: 2014 ident: CR37 article-title: Discrete bat algorithm for optimal problem of permutation flow shop scheduling publication-title: Sci World J – ident: CR38 – volume: 284 start-page: 65 year: 2010 end-page: 74 ident: CR25 article-title: A new metaheuristic bat-inspired algorithm publication-title: Nat Inspir Coop Strat Optim – volume: 83 start-page: 1 year: 2017 end-page: 17 ident: CR21 article-title: A novel bacterial foraging optimization algorithm for feature selection publication-title: Expert Syst Appl – ident: CR31 – volume: 75 start-page: 2395 issue: 5 year: 2019 end-page: 2422 ident: CR41 article-title: Hybridizing cuckoo search algorithm with bat algorithm for global numerical optimization publication-title: J Supercomput – volume: 4 start-page: 107372 year: 2021 ident: CR5 article-title: Implementing modified swarm intelligence algorithm based on slime moulds for path planning and obstacle avoidance problem in mobile robots publication-title: Appl Soft Comput – volume: 33 start-page: 1559 issue: 5 year: 2021 end-page: 1573 ident: CR29 article-title: An improved bat optimization algorithm to solve the tasks scheduling problem in open shop publication-title: Neural Comput Appl – volume: 219 issue: 4 year: 2021 ident: CR50 article-title: A novel multi population based particle swarm optimization for feature selection publication-title: Knowl-Based Syst – volume: 2017 start-page: 4367342 year: 2017 ident: CR7 article-title: GA-based membrane evolutionary algorithm for ensemble clustering publication-title: Comput Intell Neurosci – volume: 179 start-page: 2232 issue: 13 year: 2009 end-page: 2248 ident: CR16 article-title: GSA: a gravitational search algorithm publication-title: Inf Sci – volume: 13 start-page: 2932 issue: 5 year: 2013 ident: 4606_CR15 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2012.03.068 – volume: 41 start-page: 488 issue: 4 year: 2020 ident: 4606_CR43 publication-title: J Northeast Univ – volume: 258 start-page: 70 issue: 1 year: 2016 ident: 4606_CR2 publication-title: Eur J Oper Res doi: 10.1016/j.ejor.2016.07.012 – volume: 284 start-page: 65 year: 2010 ident: 4606_CR25 publication-title: Nat Inspir Coop Strat Optim – volume: 447 start-page: 64 year: 2021 ident: 4606_CR19 publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.03.077 – volume: 68 start-page: 189 issue: 1 year: 2017 ident: 4606_CR4 publication-title: J Global Optim doi: 10.1007/s10898-016-0461-1 – volume: 243 start-page: 369 issue: 2 year: 2015 ident: 4606_CR3 publication-title: Eur J Oper Res doi: 10.1016/j.ejor.2014.10.062 – volume: 5 start-page: 224 issue: 2 year: 2014 ident: 4606_CR36 publication-title: J Comput Sci doi: 10.1016/j.jocs.2013.10.002 – volume: 112 start-page: 283 year: 2012 ident: 4606_CR18 publication-title: Comput Struct doi: 10.1016/j.compstruc.2012.09.003 – volume: 7 start-page: 49 issue: 3 year: 2019 ident: 4606_CR48 publication-title: Computation doi: 10.3390/computation7030049 – volume: 152 start-page: 113377 year: 2020 ident: 4606_CR1 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2020.113377 – volume: 107 start-page: 126 year: 2018 ident: 4606_CR40 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2018.04.024 – ident: 4606_CR23 doi: 10.1109/INTELCIS.2017.8260031 – ident: 4606_CR49 doi: 10.1007/s11227-021-03773-w – ident: 4606_CR46 – volume: 33 start-page: 1559 issue: 5 year: 2021 ident: 4606_CR29 publication-title: Neural Comput Appl doi: 10.1007/s00521-020-05055-7 – volume: 19 start-page: 32 issue: 1 year: 2017 ident: 4606_CR32 publication-title: Int J Data Min Bioinform doi: 10.1504/IJDMB.2017.088538 – volume: 179 start-page: 2232 issue: 13 year: 2009 ident: 4606_CR16 publication-title: Inf Sci doi: 10.1016/j.ins.2009.03.004 – volume: 219 issue: 4 year: 2021 ident: 4606_CR50 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2021.106894 – ident: 4606_CR30 doi: 10.1051/matecconf/20167801118 – volume: 2014 start-page: 630280 year: 2014 ident: 4606_CR37 publication-title: Sci World J doi: 10.1155/2014/630280 – volume: 83 start-page: 1 year: 2017 ident: 4606_CR21 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2017.04.019 – volume: 113 start-page: 106 issue: 9 year: 2020 ident: 4606_CR28 publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2020.06.031 – volume: 449 start-page: 176 year: 2021 ident: 4606_CR35 publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.03.061 – volume: 2017 start-page: 4367342 year: 2017 ident: 4606_CR7 publication-title: Comput Intell Neurosci doi: 10.1155/2017/4367342 – volume: 25 start-page: 663 issue: 3–4 year: 2014 ident: 4606_CR26 publication-title: Neural Comput Appl doi: 10.1007/s00521-013-1525-5 – volume: 51 start-page: 1992 issue: 4 year: 2021 ident: 4606_CR42 publication-title: Appl Intell doi: 10.1007/s10489-020-01898-8 – volume: 28 start-page: 259 year: 2015 ident: 4606_CR27 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2014.11.029 – volume: 75 start-page: 2395 issue: 5 year: 2019 ident: 4606_CR41 publication-title: J Supercomput doi: 10.1007/s11227-018-2625-x – volume: 39 start-page: 11080 issue: 12 year: 2012 ident: 4606_CR17 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2012.03.066 – volume: 72 start-page: 189 year: 2018 ident: 4606_CR39 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2018.06.034 – volume: 147 start-page: 271 year: 2015 ident: 4606_CR20 publication-title: Neurocomputing doi: 10.1016/j.neucom.2014.06.067 – volume: 24 start-page: 882 issue: 5 year: 2020 ident: 4606_CR9 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2020.2968743 – volume: 177 start-page: 2075 issue: 10 year: 2007 ident: 4606_CR8 publication-title: Inf Sci doi: 10.1016/j.ins.2006.09.012 – volume: 4 start-page: 107372 year: 2021 ident: 4606_CR5 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2021.107372 – volume: 273 start-page: 448 year: 2018 ident: 4606_CR34 publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.07.039 – volume: 42 start-page: 21 issue: 1 year: 2014 ident: 4606_CR24 publication-title: Artif Intell Rev doi: 10.1007/s10462-012-9328-0 – volume: 48 start-page: 3462 issue: 10 year: 2018 ident: 4606_CR45 publication-title: Appl Intell doi: 10.1007/s10489-018-1158-6 – ident: 4606_CR14 doi: 10.1007/978-3-540-78987-1_21 – volume: 418 start-page: 561 year: 2017 ident: 4606_CR12 publication-title: Inf Sci doi: 10.1016/j.ins.2017.08.047 – volume: 28 start-page: 753 issue: 4 year: 2017 ident: 4606_CR47 publication-title: Neural Comput Appl doi: 10.1007/s00521-015-2103-9 – volume: 101 start-page: 646 year: 2019 ident: 4606_CR13 publication-title: Futur Gener Comp Syst doi: 10.1016/j.future.2019.07.015 – volume: 137 start-page: 46 year: 2019 ident: 4606_CR11 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2019.06.044 – ident: 4606_CR33 doi: 10.1007/978-981-10-4600-1_7 – volume: 16 start-page: e0260725 issue: 11 year: 2021 ident: 4606_CR44 publication-title: PLoS ONE doi: 10.1371/journal.pone.0260725 – ident: 4606_CR31 doi: 10.1016/j.protcy.2012.05.131 – ident: 4606_CR38 doi: 10.1109/IranianCIS.2014.6802527 – volume: 24 start-page: 25 year: 2015 ident: 4606_CR22 publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2015.05.003 – volume: 507 start-page: 67 year: 2020 ident: 4606_CR10 publication-title: Inf Sci doi: 10.1016/j.ins.2019.08.040 – volume: 360 start-page: 73 year: 2016 ident: 4606_CR6 publication-title: Inf Sci doi: 10.1016/j.ins.2016.03.051
SSID	ssj0004373
Score	2.34631
Snippet	The wrapper algorithm adopts the performance of the learning algorithm as the evaluation criteria to obtain excellent classification performance. However, the...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	18754
SubjectTerms	Adaptive learning Algorithms Classification Compilers Computer Science Datasets Gene expression Interpreters Machine learning Processor Architectures Programming Languages Solution space Transfer functions
Title	Global chaotic bat algorithm for feature selection
URI	https://link.springer.com/article/10.1007/s11227-022-04606-0 https://www.proquest.com/docview/2729559928
Volume	78
WOSCitedRecordID	wos000810326200004&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: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1573-0484 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004373 issn: 0920-8542 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/eLvHCXMwnV3dS8MwED90-uCL8xOnU_LgmxaWNE2bRxGHDzIEP9hbSdLUDeYma_Xv95K2FkUFfSs0Pcpdrne_Xu53AKda05AylgeJ0RoBijB4xcMAg51IpMg0NZ5d_yYejZLxWN7WTWFFc9q9KUn6L3Xb7IYy48CdPnfFPMTBq7AWObYZh9HvHttuyLCqK0sERknEWd0q872Mz-GozTG_lEV9tBl2__eeW7BZZ5fkotoO27Bi5zvQbSY3kNqRd4FVVP_ETNQClxKtSqJmT4vltJw8E8xjSW494ycp_JwcNN4ePAyv7i-vg3p6QmDQrcpAcip1FKuYagQFyv06sNwazPiUNTyWuVRGxBj_jRwIJVjOQpPTKEOThpmkKtyHznwxtwdAhNSJ5okxlGvOLNMZal1HhmcZC3MmekAbJaamphZ3Ey5maUuK7JSSolJSr5R00IOzj2deKmKNX1f3G9uktZMVKUNg4AjTWNKD88YW7e2fpR3-bfkRbDBnTt-B2IdOuXy1x7Bu3sppsTzxm-8dRCjQdQ
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dS8MwED90Cvri_MTp1Dz4poXlo2nzKOKYOIfglL2VJG3dYG6yVv9-k7S1KCroW6HpUe5yvfv1cr8DOFUKU0xI6oVaKQNQuDZXjHom2PFQ8Fhh7dj1-8FgEI5G4q5sCsuq0-5VSdJ9qetmNyMz8Ozpc1vMMzh4GVaYHbNjMfr9Y90NSYu6sjDAKPQZKVtlvpfxORzVOeaXsqiLNt3m_95zEzbK7BJdFNthC5aS2TY0q8kNqHTkHSAF1T_SYzk3S5GSOZLTp_liko-fkcljUZo4xk-UuTk5xni78NC9Gl72vHJ6gqeNW-WeYFgoP5ABVgYUSPvrIGGJNhmfTDQLRCqk5oGJ_1p0uOQkJVSn2I-NSWkssKR70JjNZ8k-IC5UqFioNWaKkYSoWARU-ZrFMaEp4S3AlRIjXVKL2wkX06gmRbZKiYxSIqeUqNOCs49nXgpijV9XtyvbRKWTZRExwMASppGwBeeVLerbP0s7-NvyE1jrDW_7Uf96cHMI68Sa1nUjtqGRL16TI1jVb_kkWxy7jfgOE1XTWQ
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dS8NADA86RXxxfuJ06j34pmW76_XjHkUdimMMv9hbubu2bjC7sVX_fnP9sCoqiG-F5kJJLiRpkl8AjpWiNmUstnytFCYorsYnblvo7FxfuKGiOkPX73q9nj8YiP6HKf6s270sSeYzDQalKUlb0zBuVYNvyN-zTCe6KexhTrwISxwzGdPUdXv3WE1G2nmNWWCS5DucFWMz3_P47JqqePNLiTTzPJ36_795HdaKqJOc5ddkAxaiZBPq5UYHUhj4FrB8BQDRQzlBUqJkSuT4aTIbpcNngvEtiaMMCZTMs_05qNRteOhc3p9fWcVWBUujuaWW4FQox5MeVZgsSPNLIeKRxkhQRpp7IhZSux7GBVq0XemymNk6pk6IqrZDQaW9A7VkkkS7QFyhfMV9rSlXnEVMhcKzlaN5GDI7Zm4DaCnQQBeQ42bzxTiowJKNUAIUSpAJJWg34OT9zDQH3PiVulnqKSiMbx4wTBgMkBrzG3Ba6qV6_TO3vb-RH8FK_6ITdK97N_uwyoxmsyHFJtTS2Ut0AMv6NR3NZ4fZnXwDbz3cPQ
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=Global+chaotic+bat+algorithm+for+feature+selection&rft.jtitle=The+Journal+of+supercomputing&rft.au=Li%2C+Ying&rft.au=Cui+Xueting&rft.au=Fan+Jiahao&rft.au=Wang%2C+Tan&rft.date=2022-11-01&rft.pub=Springer+Nature+B.V&rft.issn=0920-8542&rft.eissn=1573-0484&rft.volume=78&rft.issue=17&rft.spage=18754&rft.epage=18776&rft_id=info:doi/10.1007%2Fs11227-022-04606-0&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0920-8542&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0920-8542&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0920-8542&client=summon