An adaptive second order fuzzy neural network for nonlinear system modeling
In this paper, an adaptive second order algorithm (ASOA) has been developed to train the fuzzy neural network (FNN) to achieve fast and robust convergence for nonlinear system modeling. Different from recent studies, this ASOA-based FNN (ASOA-FNN) has the quasi Hessian matrix and gradient vector whi...
Gespeichert in:
| Veröffentlicht in: | Neurocomputing (Amsterdam) Jg. 214; S. 837 - 847 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier B.V
19.11.2016
|
| Schlagworte: | |
| ISSN: | 0925-2312, 1872-8286 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | In this paper, an adaptive second order algorithm (ASOA) has been developed to train the fuzzy neural network (FNN) to achieve fast and robust convergence for nonlinear system modeling. Different from recent studies, this ASOA-based FNN (ASOA-FNN) has the quasi Hessian matrix and gradient vector which are accumulated as the sum of related sub matrices and vectors, respectively. Meanwhile, the learning rate of ASOA-FNN is designed to accelerate the learning speed. In addition, the convergence of the proposed ASOA-FNN has been proved both in the fixed learning rate phase and the adaptive learning rate phase. Finally, several comparisons have been realized and they have shown that the proposed ASOA-FNN has faster convergence speed and more accurate results than that of some existing methods. |
|---|---|
| AbstractList | In this paper, an adaptive second order algorithm (ASOA) has been developed to train the fuzzy neural network (FNN) to achieve fast and robust convergence for nonlinear system modeling. Different from recent studies, this ASOA-based FNN (ASOA-FNN) has the quasi Hessian matrix and gradient vector which are accumulated as the sum of related sub matrices and vectors, respectively. Meanwhile, the learning rate of ASOA-FNN is designed to accelerate the learning speed. In addition, the convergence of the proposed ASOA-FNN has been proved both in the fixed learning rate phase and the adaptive learning rate phase. Finally, several comparisons have been realized and they have shown that the proposed ASOA-FNN has faster convergence speed and more accurate results than that of some existing methods. |
| Author | Qiao, Jun-Fei Ge, Lu-Ming Han, Hong-Gui |
| Author_xml | – sequence: 1 givenname: Hong-Gui surname: Han fullname: Han, Hong-Gui email: Rechardhan@sina.com organization: College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China – sequence: 2 givenname: Lu-Ming surname: Ge fullname: Ge, Lu-Ming email: geluming1992@126.com organization: College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China – sequence: 3 givenname: Jun-Fei surname: Qiao fullname: Qiao, Jun-Fei email: isibox@sina.com organization: College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China |
| BookMark | eNqFkM1KAzEURoNUsK2-gYu8wIxJpjOZuBBK8Q8LbnQdMsmNpE4nJUkr7dObUlcudPVxL5zvcs8EjQY_AELXlJSU0OZmVQ6w1X5dsjyVhJeEVGdoTFvOipa1zQiNiWB1wSrKLtAkxhUhlFMmxuhlPmBl1Ca5HeAI2g8G-2AgYLs9HPY4FwfV50hfPnxi6wPOx3s3gAo47mOCNV57A3nzcYnOreojXP3kFL0_3L8tnorl6-PzYr4sdEWaVGjRUSPqpiWU5iAdEUpYa2a2g7oSbcesqTlXRlBqrFCc1mYGHHjXWm2Fqabo9tSrg48xgJXaJZWcH1JQrpeUyKMWuZInLfKoRRIus5YMz37Bm-DWKuz_w-5OGOTHdg6CjNrBoMG4ADpJ493fBd8Ya4Lw |
| CitedBy_id | crossref_primary_10_1016_j_neucom_2019_07_004 crossref_primary_10_1109_TIE_2021_3056998 crossref_primary_10_1016_j_neucom_2018_02_049 crossref_primary_10_1016_j_asoc_2020_106516 crossref_primary_10_1109_TFUZZ_2022_3185464 crossref_primary_10_5004_dwt_2019_23360 crossref_primary_10_1016_j_knosys_2025_113674 crossref_primary_10_1007_s10845_023_02254_6 crossref_primary_10_1007_s00521_021_06838_2 crossref_primary_10_1109_TSMC_2018_2812156 crossref_primary_10_1016_j_neucom_2019_01_073 crossref_primary_10_1016_j_neucom_2017_02_008 crossref_primary_10_1016_j_knosys_2018_04_014 crossref_primary_10_1007_s10489_020_01645_z crossref_primary_10_1016_j_apenergy_2016_11_074 crossref_primary_10_1016_j_cjche_2018_03_027 crossref_primary_10_1109_TII_2020_3034335 crossref_primary_10_1016_j_oceaneng_2021_110265 crossref_primary_10_1109_TIE_2017_2777415 crossref_primary_10_1057_s41272_020_00253_3 crossref_primary_10_1016_j_neucom_2017_08_059 crossref_primary_10_1016_j_jwpe_2020_101763 crossref_primary_10_1016_j_neunet_2017_10_006 crossref_primary_10_1016_j_asoc_2024_111458 crossref_primary_10_1371_journal_pone_0224075 crossref_primary_10_1016_j_neucom_2018_01_001 crossref_primary_10_1016_j_amc_2021_125994 crossref_primary_10_1016_j_neucom_2017_02_038 crossref_primary_10_3233_JIFS_189431 crossref_primary_10_1016_j_jprocont_2018_05_002 crossref_primary_10_1016_j_fss_2019_02_010 crossref_primary_10_1016_j_asoc_2021_108258 crossref_primary_10_1016_j_hazadv_2022_100224 crossref_primary_10_1016_j_neucom_2017_05_065 crossref_primary_10_1109_TFUZZ_2017_2718497 |
| Cites_doi | 10.1016/j.neucom.2013.12.031 10.1016/j.compeleceng.2014.08.011 10.1016/j.asoc.2015.06.046 10.1109/TFUZZ.2012.2200900 10.1016/j.neunet.2015.03.010 10.1016/j.biortech.2014.05.024 10.1109/TNNLS.2014.2329097 10.1109/TNN.2010.2066285 10.1016/j.neucom.2014.07.021 10.1109/TNN.2010.2045657 10.1109/TFUZZ.2012.2193587 10.1109/TSMCC.2009.2016572 10.1109/TCYB.2013.2260537 10.1016/j.neucom.2015.03.104 10.1016/j.jprocont.2012.04.002 10.1016/j.fss.2008.12.018 10.1016/j.neucom.2015.06.073 10.1016/j.neucom.2012.11.013 10.1109/TNN.2002.1031939 10.1016/j.fss.2008.11.022 10.1109/TNN.2004.824250 10.1109/TIE.2010.2076415 10.1016/j.fss.2011.02.004 10.1109/TNNLS.2014.2306915 10.1016/j.automatica.2015.02.019 10.1016/j.automatica.2012.05.034 10.1016/j.neucom.2012.07.048 10.1016/j.neucom.2009.05.006 10.1016/j.ins.2013.10.035 10.1109/TFUZZ.2011.2175932 10.1109/TFUZZ.2014.2336263 10.1016/j.watres.2013.07.001 10.1016/j.fss.2010.06.002 10.1016/j.asoc.2009.03.011 10.1109/TFUZZ.2010.2070841 |
| ContentType | Journal Article |
| Copyright | 2016 Elsevier B.V. |
| Copyright_xml | – notice: 2016 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.neucom.2016.07.003 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1872-8286 |
| EndPage | 847 |
| ExternalDocumentID | 10_1016_j_neucom_2016_07_003 S0925231216307329 |
| GrantInformation_xml | – fundername: National Science Foundation of China grantid: 61533002; 61225016 funderid: http://dx.doi.org/10.13039/501100001809 – fundername: China Postdoctoral Science Foundation grantid: 2014M550017 funderid: http://dx.doi.org/10.13039/501100002858 – fundername: Collaborative Innovation Program grantid: ZH14000177 – fundername: Beijing Municipal Education Commission Foundation grantid: km201410005001; KZ201410005002 funderid: http://dx.doi.org/10.13039/501100003213 – fundername: pH.D. Program Foundation from Ministry of Chinese Education grantid: 20121103120020; 20131103110016 funderid: http://dx.doi.org/10.13039/501100002338 – fundername: Beijing Nova Program grantid: Z131104000413007 funderid: http://dx.doi.org/10.13039/501100005090 – fundername: Beijing Postdoctoral Research Foundation grantid: 2015ZZ-03 funderid: http://dx.doi.org/10.13039/501100005024 |
| GroupedDBID | --- --K --M .DC .~1 0R~ 123 1B1 1~. 1~5 4.4 457 4G. 53G 5VS 7-5 71M 8P~ 9JM 9JN AABNK AACTN AADPK AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAXLA AAXUO AAYFN ABBOA ABCQJ ABFNM ABJNI ABMAC ABYKQ ACDAQ ACGFS ACRLP ACZNC ADBBV ADEZE AEBSH AEKER AENEX AFKWA AFTJW AFXIZ AGHFR AGUBO AGWIK AGYEJ AHHHB AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD AXJTR BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ IHE J1W KOM LG9 M41 MO0 MOBAO N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RIG ROL RPZ SDF SDG SDP SES SPC SPCBC SSN SSV SSZ T5K ZMT ~G- 29N 9DU AAQXK AATTM AAXKI AAYWO AAYXX ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADJOM ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS FEDTE FGOYB HLZ HVGLF HZ~ R2- SBC SEW WUQ XPP ~HD |
| ID | FETCH-LOGICAL-c306t-c9b1d95680119560b09a9ffd4fbe5398b2fd577ad911df9a715d4e7e7b8fcf9d3 |
| ISICitedReferencesCount | 38 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000386741300079&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0925-2312 |
| IngestDate | Sat Nov 29 07:13:24 EST 2025 Tue Nov 18 22:38:10 EST 2025 Fri Feb 23 02:30:25 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Nonlinear system modeling Fast convergence Fuzzy neural network Adaptive second-order algorithm |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c306t-c9b1d95680119560b09a9ffd4fbe5398b2fd577ad911df9a715d4e7e7b8fcf9d3 |
| PageCount | 11 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_neucom_2016_07_003 crossref_primary_10_1016_j_neucom_2016_07_003 elsevier_sciencedirect_doi_10_1016_j_neucom_2016_07_003 |
| PublicationCentury | 2000 |
| PublicationDate | 2016-11-19 |
| PublicationDateYYYYMMDD | 2016-11-19 |
| PublicationDate_xml | – month: 11 year: 2016 text: 2016-11-19 day: 19 |
| PublicationDecade | 2010 |
| PublicationTitle | Neurocomputing (Amsterdam) |
| PublicationYear | 2016 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Cpałka, Łapa, Przybył, Zalasiński (bib5) 2014; 135 Meng, Pei (bib20) 2014; 125 Han, Qiao (bib38) 2012; 22 Wilamowski, Yu (bib29) 2010; 21 Pizzileo, Li, Irwin, Zhao (bib32) 2012; 20 Martínez-Garcia, Olguín, Fall (bib37) 2014; 166 Liu, Li (bib11) 2004; 15 Sanz, Bernardo, Herrera, Bustince, Hagras (bib26) 2015; 23 Bhattacharya, Konar, Das (bib6) 2016; 171 Pratama, Er, Li, Li, Oentaryo, Lughofer, Arifin (bib2) 2013; 110 Mashinchi, Selamat (bib13) 2009; 9 Juang, Hsieh (bib35) 2009; 160 Han, Li, Qiao (bib7) 2014; 40 Han, Qiao (bib27) 2010; 18 Chen, Lin, Lin (bib16) 2009; 39 Lu (bib31) 2011; 58 Wang, Meng, Meng (bib34) 2009; 72 Yilmaz, Oysal (bib23) 2010; 21 Meng, Pei (bib10) 2014; 125 Davanipoor, Zekri, Sheikholeslam (bib33) 2012; 20 Zhao, Li, Irwin (bib22) 2013; 21 Alieva, Guirimova, Fazlollahib, Alievc (bib17) 2009; 160 Chen, Wang, Wang, Chen (bib24) 2014; 25 Tzeng (bib12) 2010; 161 Wu, Li, Quevedo, Lau, Shi (bib4) 2015; 54 Ebadzadeh, Salimi-Badr (bib25) 2015; 148 Fan, Zeng, Levenberg-Marquardt (bib28) 2013; 219 Ampazis, Perantonis (bib30) 2002; 13 Melo, Watada (bib15) 2016; 172 Qiao, Han (bib3) 2012; 48 Eshtiaghi, Markis, Yap, Baudez, Slatter (bib36) 2013; 47 Ebadzadeh, Salimi-Badr (bib1) 2015; 148 Lee, Li, Chang (bib21) 2011; 171 Dahal, Almejalli, Hossain, Chen (bib19) 2015; 35 Tan, Watada, Ibrahim, Khalid (bib18) 2015; 26 Kuo, Hung, Cheng (bib14) 2014; 262 Han, Wu, Qiao (bib9) 2014; 44 Wang, Yu, Li, Wang, Huang, Huang (bib8) 2015; 67 Wu (10.1016/j.neucom.2016.07.003_bib4) 2015; 54 Tzeng (10.1016/j.neucom.2016.07.003_bib12) 2010; 161 Fan (10.1016/j.neucom.2016.07.003_bib28) 2013; 219 Davanipoor (10.1016/j.neucom.2016.07.003_bib33) 2012; 20 Juang (10.1016/j.neucom.2016.07.003_bib35) 2009; 160 Eshtiaghi (10.1016/j.neucom.2016.07.003_bib36) 2013; 47 Chen (10.1016/j.neucom.2016.07.003_bib16) 2009; 39 Yilmaz (10.1016/j.neucom.2016.07.003_bib23) 2010; 21 Sanz (10.1016/j.neucom.2016.07.003_bib26) 2015; 23 Martínez-Garcia (10.1016/j.neucom.2016.07.003_bib37) 2014; 166 Meng (10.1016/j.neucom.2016.07.003_bib10) 2014; 125 Lee (10.1016/j.neucom.2016.07.003_bib21) 2011; 171 Chen (10.1016/j.neucom.2016.07.003_bib24) 2014; 25 Kuo (10.1016/j.neucom.2016.07.003_bib14) 2014; 262 Bhattacharya (10.1016/j.neucom.2016.07.003_bib6) 2016; 171 Melo (10.1016/j.neucom.2016.07.003_bib15) 2016; 172 Meng (10.1016/j.neucom.2016.07.003_bib20) 2014; 125 Han (10.1016/j.neucom.2016.07.003_bib38) 2012; 22 Liu (10.1016/j.neucom.2016.07.003_bib11) 2004; 15 Cpałka (10.1016/j.neucom.2016.07.003_bib5) 2014; 135 Ebadzadeh (10.1016/j.neucom.2016.07.003_bib1) 2015; 148 Pratama (10.1016/j.neucom.2016.07.003_bib2) 2013; 110 Alieva (10.1016/j.neucom.2016.07.003_bib17) 2009; 160 Han (10.1016/j.neucom.2016.07.003_bib27) 2010; 18 Wang (10.1016/j.neucom.2016.07.003_bib34) 2009; 72 Tan (10.1016/j.neucom.2016.07.003_bib18) 2015; 26 Ampazis (10.1016/j.neucom.2016.07.003_bib30) 2002; 13 Pizzileo (10.1016/j.neucom.2016.07.003_bib32) 2012; 20 Wilamowski (10.1016/j.neucom.2016.07.003_bib29) 2010; 21 Han (10.1016/j.neucom.2016.07.003_bib7) 2014; 40 Wang (10.1016/j.neucom.2016.07.003_bib8) 2015; 67 Lu (10.1016/j.neucom.2016.07.003_bib31) 2011; 58 Ebadzadeh (10.1016/j.neucom.2016.07.003_bib25) 2015; 148 Qiao (10.1016/j.neucom.2016.07.003_bib3) 2012; 48 Mashinchi (10.1016/j.neucom.2016.07.003_bib13) 2009; 9 Han (10.1016/j.neucom.2016.07.003_bib9) 2014; 44 Zhao (10.1016/j.neucom.2016.07.003_bib22) 2013; 21 Dahal (10.1016/j.neucom.2016.07.003_bib19) 2015; 35 |
| References_xml | – volume: 262 start-page: 78 year: 2014 end-page: 98 ident: bib14 article-title: Application of an optimization artificial immune network and particle swarm optimization-based fuzzy neural network to an RFID-based positioning system publication-title: Inf. Sci. – volume: 22 start-page: 1103 year: 2012 end-page: 1112 ident: bib38 article-title: Prediction of activated sludge bulking based on a self-organizing RBF neural network publication-title: J. Process Control – volume: 25 start-page: 1741 year: 2014 end-page: 1757 ident: bib24 article-title: A new learning algorithm for a fully connected neuro-fuzzy inference system publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 161 start-page: 2585 year: 2010 end-page: 2596 ident: bib12 article-title: Design of fuzzy wavelet neural networks using the GA approach for function approximation and system identification publication-title: Fuzzy Sets Syst. – volume: 9 start-page: 1208 year: 2009 end-page: 1216 ident: bib13 article-title: An improvement on genetic-based learning method for fuzzy artificial neural networks publication-title: Appl. Soft Comput. – volume: 135 start-page: 203 year: 2014 end-page: 217 ident: bib5 article-title: A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects publication-title: Neurocomputing – volume: 15 start-page: 545 year: 2004 end-page: 558 ident: bib11 article-title: Efficient learning algorithms for three-layer regular feedforward fuzzy neural networks publication-title: IEEE Trans. Neural Netw. – volume: 172 start-page: 405 year: 2016 end-page: 412 ident: bib15 article-title: Gaussian-PSO with fuzzy reasoning based on structural learning for training a neural network publication-title: Neurocomputing – volume: 110 start-page: 18 year: 2013 end-page: 28 ident: bib2 article-title: Data driven modeling based on dynamic parsimonious fuzzy neural network publication-title: Neurocomputing – volume: 21 start-page: 930 year: 2010 end-page: 937 ident: bib29 article-title: Improved computation for Levenberg-Marquardt training publication-title: IEEE Trans. Neural Netw. – volume: 40 start-page: 2216 year: 2014 end-page: 2226 ident: bib7 article-title: A fuzzy neural network approach for online fault detection in waste water treatment process publication-title: Comput. Electr. Eng. – volume: 20 start-page: 1076 year: 2012 end-page: 1089 ident: bib32 article-title: Improved structure optimization for fuzzy-neural networks publication-title: IEEE Trans. Fuzzy Syst. – volume: 171 start-page: 22 year: 2011 end-page: 43 ident: bib21 article-title: A species-based improved electromagnetism-like mechanism algorithm for Tsk-Type interval-valued neural fuzzy system optimization publication-title: Fuzzy Sets Syst. – volume: 13 start-page: 1064 year: 2002 end-page: 1074 ident: bib30 article-title: Two highly efficient second-order algorithms for training feedforward networks publication-title: IEEE Trans. Neural Netw. – volume: 26 start-page: 933 year: 2015 end-page: 950 ident: bib18 article-title: Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 125 start-page: 88 year: 2014 end-page: 94 ident: bib10 article-title: Dynamic adaptive learning algorithm based on two-fuzzy neural-networks publication-title: Neurocomputing – volume: 21 start-page: 1599 year: 2010 end-page: 1609 ident: bib23 article-title: Fuzzy wavelet neural network models for prediction and identification of dynamical systems publication-title: IEEE Trans. Neural Netw. – volume: 48 start-page: 1729 year: 2012 end-page: 1734 ident: bib3 article-title: Identification and modeling of nonlinear dynamical systems using a novel self-organizing RBF-based approach publication-title: Automatica – volume: 171 start-page: 551 year: 2016 end-page: 568 ident: bib6 article-title: Secondary factor induced stock index time-series prediction using Self-Adaptive Interval Type-2 Fuzzy Sets publication-title: Neurocomputing – volume: 166 start-page: 112 year: 2014 end-page: 119 ident: bib37 article-title: Aerobic stabilization of biological sludge characterized by an extremely low decay rate: modeling, identifiability analysis and parameter estimation publication-title: Bioresour. Technol. – volume: 21 start-page: 30 year: 2013 end-page: 44 ident: bib22 article-title: A new gradient descent approach for local learning of fuzzy neural models publication-title: IEEE Trans. Fuzzy Syst. – volume: 23 start-page: 973 year: 2015 end-page: 990 ident: bib26 article-title: A compact evolutionary interval-valued fuzzy rule-based classification system for the modeling and prediction of real-world financial applications with imbalanced data publication-title: IEEE Trans. Fuzzy Syst. – volume: 58 start-page: 3046 year: 2011 end-page: 3058 ident: bib31 article-title: Wavelet fuzzy neural networks for identification and predictive control of dynamic systems publication-title: IEEE Trans. Ind. Electron. – volume: 39 start-page: 459 year: 2009 end-page: 473 ident: bib16 article-title: Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution publication-title: IEEE Trans. Syst. Man Cybern.-Part C: Appl. Rev. – volume: 20 start-page: 463 year: 2012 end-page: 470 ident: bib33 article-title: Fuzzy wavelet neural network with an accelerated hybrid learning algorithm publication-title: IEEE Trans. Fuzzy Syst. – volume: 72 start-page: 3818 year: 2009 end-page: 3829 ident: bib34 article-title: A fast and accurate online self-organizing scheme for parsimonious fuzzy neural networks publication-title: Neurocomputing – volume: 148 start-page: 430 year: 2015 end-page: 444 ident: bib1 article-title: CFNN: correlated fuzzy neural network publication-title: Neurocomputing – volume: 44 start-page: 554 year: 2014 end-page: 564 ident: bib9 article-title: Nonlinear systems modeling based on self-organizing fuzzy-neural-network with adaptive computation algorithm publication-title: IEEE Trans. Cybern. – volume: 160 start-page: 2486 year: 2009 end-page: 2504 ident: bib35 article-title: TS-fuzzy system-based support vector regression publication-title: Fuzzy Sets Syst. – volume: 160 start-page: 2553 year: 2009 end-page: 2566 ident: bib17 article-title: Evolutionary algorithm-based learning of fuzzy neural networks. Part 2: Recurrent fuzzy neural networks publication-title: Fuzzy Sets Syst. – volume: 148 start-page: 430 year: 2015 end-page: 444 ident: bib25 article-title: CFNN: Correlated fuzzy neural network publication-title: Neurocomputing – volume: 219 start-page: 9438 year: 2013 end-page: 9446 ident: bib28 article-title: algorithm with correction for singular system of nonlinear equations publication-title: Appl. Math. Comput. – volume: 67 start-page: 84 year: 2015 end-page: 91 ident: bib8 article-title: Robust stability of stochastic fuzzy delayed neural networks with impulsive time window publication-title: Neural Netw. – volume: 35 start-page: 605 year: 2015 end-page: 617 ident: bib19 article-title: GA-based learning for rule identification in fuzzy neural networks publication-title: Appl. Soft Comput. – volume: 125 start-page: 88 year: 2014 end-page: 94 ident: bib20 article-title: Dynamic adaptive learning algorithm based on two-fuzzy neural-networks publication-title: Neurocomputing – volume: 18 start-page: 1129 year: 2010 end-page: 1143 ident: bib27 article-title: A self-organizing fuzzy neural network based on a growing-and-pruning algorithm publication-title: IEEE Trans. Fuzzy Syst. – volume: 47 start-page: 5493 year: 2013 end-page: 5510 ident: bib36 article-title: Rheological characterization of municipal sludge: a review publication-title: Water Res. – volume: 54 start-page: 332 year: 2015 end-page: 339 ident: bib4 article-title: Data-driven power control for state estimation: a Bayesian inference approach publication-title: Automatica – volume: 135 start-page: 203 issue: 1 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib5 article-title: A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects publication-title: Neurocomputing doi: 10.1016/j.neucom.2013.12.031 – volume: 40 start-page: 2216 issue: 7 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib7 article-title: A fuzzy neural network approach for online fault detection in waste water treatment process publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2014.08.011 – volume: 35 start-page: 605 issue: 1 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib19 article-title: GA-based learning for rule identification in fuzzy neural networks publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.06.046 – volume: 21 start-page: 30 issue: 1 year: 2013 ident: 10.1016/j.neucom.2016.07.003_bib22 article-title: A new gradient descent approach for local learning of fuzzy neural models publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2012.2200900 – volume: 67 start-page: 84 issue: 1 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib8 article-title: Robust stability of stochastic fuzzy delayed neural networks with impulsive time window publication-title: Neural Netw. doi: 10.1016/j.neunet.2015.03.010 – volume: 166 start-page: 112 issue: 8 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib37 article-title: Aerobic stabilization of biological sludge characterized by an extremely low decay rate: modeling, identifiability analysis and parameter estimation publication-title: Bioresour. Technol. doi: 10.1016/j.biortech.2014.05.024 – volume: 26 start-page: 933 issue: 5 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib18 article-title: Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2014.2329097 – volume: 21 start-page: 1599 issue: 10 year: 2010 ident: 10.1016/j.neucom.2016.07.003_bib23 article-title: Fuzzy wavelet neural network models for prediction and identification of dynamical systems publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2010.2066285 – volume: 148 start-page: 430 issue: 1 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib1 article-title: CFNN: correlated fuzzy neural network publication-title: Neurocomputing doi: 10.1016/j.neucom.2014.07.021 – volume: 21 start-page: 930 issue: 6 year: 2010 ident: 10.1016/j.neucom.2016.07.003_bib29 article-title: Improved computation for Levenberg-Marquardt training publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2010.2045657 – volume: 20 start-page: 1076 issue: 6 year: 2012 ident: 10.1016/j.neucom.2016.07.003_bib32 article-title: Improved structure optimization for fuzzy-neural networks publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2012.2193587 – volume: 39 start-page: 459 issue: 4 year: 2009 ident: 10.1016/j.neucom.2016.07.003_bib16 article-title: Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution publication-title: IEEE Trans. Syst. Man Cybern.-Part C: Appl. Rev. doi: 10.1109/TSMCC.2009.2016572 – volume: 44 start-page: 554 issue: 4 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib9 article-title: Nonlinear systems modeling based on self-organizing fuzzy-neural-network with adaptive computation algorithm publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2013.2260537 – volume: 172 start-page: 405 issue: 1 year: 2016 ident: 10.1016/j.neucom.2016.07.003_bib15 article-title: Gaussian-PSO with fuzzy reasoning based on structural learning for training a neural network publication-title: Neurocomputing doi: 10.1016/j.neucom.2015.03.104 – volume: 22 start-page: 1103 issue: 6 year: 2012 ident: 10.1016/j.neucom.2016.07.003_bib38 article-title: Prediction of activated sludge bulking based on a self-organizing RBF neural network publication-title: J. Process Control doi: 10.1016/j.jprocont.2012.04.002 – volume: 160 start-page: 2553 issue: 17 year: 2009 ident: 10.1016/j.neucom.2016.07.003_bib17 article-title: Evolutionary algorithm-based learning of fuzzy neural networks. Part 2: Recurrent fuzzy neural networks publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2008.12.018 – volume: 171 start-page: 551 issue: 1 year: 2016 ident: 10.1016/j.neucom.2016.07.003_bib6 article-title: Secondary factor induced stock index time-series prediction using Self-Adaptive Interval Type-2 Fuzzy Sets publication-title: Neurocomputing doi: 10.1016/j.neucom.2015.06.073 – volume: 110 start-page: 18 issue: 1 year: 2013 ident: 10.1016/j.neucom.2016.07.003_bib2 article-title: Data driven modeling based on dynamic parsimonious fuzzy neural network publication-title: Neurocomputing doi: 10.1016/j.neucom.2012.11.013 – volume: 219 start-page: 9438 issue: 17 year: 2013 ident: 10.1016/j.neucom.2016.07.003_bib28 article-title: algorithm with correction for singular system of nonlinear equations publication-title: Appl. Math. Comput. – volume: 13 start-page: 1064 issue: 5 year: 2002 ident: 10.1016/j.neucom.2016.07.003_bib30 article-title: Two highly efficient second-order algorithms for training feedforward networks publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2002.1031939 – volume: 160 start-page: 2486 issue: 17 year: 2009 ident: 10.1016/j.neucom.2016.07.003_bib35 article-title: TS-fuzzy system-based support vector regression publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2008.11.022 – volume: 15 start-page: 545 issue: 3 year: 2004 ident: 10.1016/j.neucom.2016.07.003_bib11 article-title: Efficient learning algorithms for three-layer regular feedforward fuzzy neural networks publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2004.824250 – volume: 58 start-page: 3046 issue: 7 year: 2011 ident: 10.1016/j.neucom.2016.07.003_bib31 article-title: Wavelet fuzzy neural networks for identification and predictive control of dynamic systems publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2010.2076415 – volume: 171 start-page: 22 issue: 1 year: 2011 ident: 10.1016/j.neucom.2016.07.003_bib21 article-title: A species-based improved electromagnetism-like mechanism algorithm for Tsk-Type interval-valued neural fuzzy system optimization publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2011.02.004 – volume: 25 start-page: 1741 issue: 10 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib24 article-title: A new learning algorithm for a fully connected neuro-fuzzy inference system publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2014.2306915 – volume: 54 start-page: 332 issue: 1 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib4 article-title: Data-driven power control for state estimation: a Bayesian inference approach publication-title: Automatica doi: 10.1016/j.automatica.2015.02.019 – volume: 48 start-page: 1729 issue: 8 year: 2012 ident: 10.1016/j.neucom.2016.07.003_bib3 article-title: Identification and modeling of nonlinear dynamical systems using a novel self-organizing RBF-based approach publication-title: Automatica doi: 10.1016/j.automatica.2012.05.034 – volume: 125 start-page: 88 issue: 1 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib10 article-title: Dynamic adaptive learning algorithm based on two-fuzzy neural-networks publication-title: Neurocomputing doi: 10.1016/j.neucom.2012.07.048 – volume: 72 start-page: 3818 issue: 16–18 year: 2009 ident: 10.1016/j.neucom.2016.07.003_bib34 article-title: A fast and accurate online self-organizing scheme for parsimonious fuzzy neural networks publication-title: Neurocomputing doi: 10.1016/j.neucom.2009.05.006 – volume: 262 start-page: 78 issue: 3 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib14 article-title: Application of an optimization artificial immune network and particle swarm optimization-based fuzzy neural network to an RFID-based positioning system publication-title: Inf. Sci. doi: 10.1016/j.ins.2013.10.035 – volume: 20 start-page: 463 issue: 3 year: 2012 ident: 10.1016/j.neucom.2016.07.003_bib33 article-title: Fuzzy wavelet neural network with an accelerated hybrid learning algorithm publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2011.2175932 – volume: 125 start-page: 88 issue: 1 year: 2014 ident: 10.1016/j.neucom.2016.07.003_bib20 article-title: Dynamic adaptive learning algorithm based on two-fuzzy neural-networks publication-title: Neurocomputing doi: 10.1016/j.neucom.2012.07.048 – volume: 23 start-page: 973 issue: 4 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib26 article-title: A compact evolutionary interval-valued fuzzy rule-based classification system for the modeling and prediction of real-world financial applications with imbalanced data publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2014.2336263 – volume: 47 start-page: 5493 issue: 15 year: 2013 ident: 10.1016/j.neucom.2016.07.003_bib36 article-title: Rheological characterization of municipal sludge: a review publication-title: Water Res. doi: 10.1016/j.watres.2013.07.001 – volume: 161 start-page: 2585 issue: 19 year: 2010 ident: 10.1016/j.neucom.2016.07.003_bib12 article-title: Design of fuzzy wavelet neural networks using the GA approach for function approximation and system identification publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2010.06.002 – volume: 9 start-page: 1208 issue: 4 year: 2009 ident: 10.1016/j.neucom.2016.07.003_bib13 article-title: An improvement on genetic-based learning method for fuzzy artificial neural networks publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2009.03.011 – volume: 18 start-page: 1129 issue: 6 year: 2010 ident: 10.1016/j.neucom.2016.07.003_bib27 article-title: A self-organizing fuzzy neural network based on a growing-and-pruning algorithm publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2010.2070841 – volume: 148 start-page: 430 issue: 1 year: 2015 ident: 10.1016/j.neucom.2016.07.003_bib25 article-title: CFNN: Correlated fuzzy neural network publication-title: Neurocomputing doi: 10.1016/j.neucom.2014.07.021 |
| SSID | ssj0017129 |
| Score | 2.3696055 |
| Snippet | In this paper, an adaptive second order algorithm (ASOA) has been developed to train the fuzzy neural network (FNN) to achieve fast and robust convergence for... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 837 |
| SubjectTerms | Adaptive second-order algorithm Fast convergence Fuzzy neural network Nonlinear system modeling |
| Title | An adaptive second order fuzzy neural network for nonlinear system modeling |
| URI | https://dx.doi.org/10.1016/j.neucom.2016.07.003 |
| Volume | 214 |
| WOSCitedRecordID | wos000386741300079&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-8286 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017129 issn: 0925-2312 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELZgy4ELb0ShIB-4rYzycGL7GFV98Ko4FGlvkRPbaFdgVt0NKv31Hb-yC0WFHrhEUZTYu55PM-OZ8TcIvQabn3UVN0RnmhPaZ4qIuqIkL3MFOtlwqn3Xkg_s5ITPZuJTTLSvfDsBZi0_PxfL_ypqeAbCdkdnbyDucVB4APcgdLiC2OH6T4Jv7FQqufQlQSu33VVTz685NcPFxc-pI7AEsdhQ_u2rDG2gy5CJ1zm0x0k2bZH4nQawdb4HRIwuNN8cyYJyiBIbRea12PF3-4UcDfOxuie0cx7IxzSqi7XOZUj7DJYc6vl2_CGv3UG8qOViILGoCHiJv-jUIqdbWpEHXpdkYAPF5hXdHcIIizewDq6Qx83leVWzcmOrUn7-NxM2FhammrVFG0Zp3Sht5nLs5W20U7BK8Anaad4ezN6NySaWF4GSMf6RdMLSlwFe_TV_9mC2vJLTB-he3E7gJsDgIbql7SN0P7XqwFFzP0bvG4sTKnBABfaowB4VOKACR1RgQAUeUYEDKnBCxRP0-fDgdP-YxD4apIcN4Zr0osuVOxbq-f3qrMuEFMYoajpdlYJ3hVEVY1KB4VNGSJZXimqmWcdNb4Qqn6IJzKmfIdyBhyepKFWuFK27UtRG1oWSOqNKgLe5i8q0Nm0fSeZdr5Ov7XWS2UVk_GoZSFb-8j5Ly95GRzE4gC1g6dovn99wphfo7gbze2iyPhv0S3Sn_7Ger85eRSBdArjCjP8 |
| linkProvider | Elsevier |
| 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=An+adaptive+second+order+fuzzy+neural+network+for+nonlinear+system+modeling&rft.jtitle=Neurocomputing+%28Amsterdam%29&rft.au=Han%2C+Hong-Gui&rft.au=Ge%2C+Lu-Ming&rft.au=Qiao%2C+Jun-Fei&rft.date=2016-11-19&rft.issn=0925-2312&rft.volume=214&rft.spage=837&rft.epage=847&rft_id=info:doi/10.1016%2Fj.neucom.2016.07.003&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_neucom_2016_07_003 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0925-2312&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0925-2312&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0925-2312&client=summon |