Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling
- Author
- CHUNSHIEN LI1 ; CHENG, Kuo-Hsiang2
[1] Department of Computer Science and Information Engineering, National University of Tainan, 33, Sec. 2, Shu-Lin St, Tainan 700, Taiwan, Province of China
[2] Department of Electrical Engineering, Chang Gung University, 259, Wen-Hwa 1st Road, Kwei-Shan, Tao-Yuan 333, Taiwan, Province of China - Source
Fuzzy sets and systems. 2007, Vol 158, Num 2, pp 194-212, 19 p ; ref : 26 ref
- CODEN
- FSSYD8
- ISSN
- 0165-0114
- Scientific domain
- Control theory, operational research; Computer science; Mathematics
- Publisher
- Elsevier, Amsterdam
- Publication country
- Netherlands
- Document type
- Article
- Language
- English
- Author keyword
- Hybrid learning (HL);'Random optimization (RO) Least square estimation (LSE) Modeling Recurrent neuro-fuzzy system (RNFS) System identification
- Keyword (fr)
- Algorithme apprentissage Apprentissage Boucle réaction Convergence Ensemble flou Identification système Ingénierie Méthode moindre carré Méthode optimisation Réseau neuronal Système flou Traitement information 28Bxx 28Cxx 49XX 65Kxx
- Keyword (en)
- Learning algorithm Learning Feedback Convergence Fuzzy set System identification Engineering Least squares method Optimization method Neural network Fuzzy system Information processing
- Keyword (es)
- Algoritmo aprendizaje Aprendizaje Retroalimentación Convergencia Conjunto difuso Identificación sistema Ingeniería Método cuadrado menor Método optimización Red neuronal Sistema difuso Procesamiento información
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02A Theoretical computing / 001D02A08 Miscellaneous
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02D Control theory. Systems / 001D02D02 System theory
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D03 Electronics / 001D03G Electric, optical and optoelectronic circuits / 001D03G02 Circuit properties / 001D03G02A Electronic circuits / 001D03G02A6 Digital circuits
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D04 Telecommunications and information theory / 001D04A Information, signal and communications theory / 001D04A02 Mathematical methods
- Discipline
- Computer science : theoretical automation and systems Electronics Telecommunications and information theory
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 18410689
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Access to the document
Install on your browser
DOI
10.1016/j.fss.2006.09.002 
https://dx.doi.org/10.1016/j.fss.2006.09.002
"O:13:\"PanistOpenUrl\":36:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000idc\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1016\/j.fss.2006.09.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:9:\"\u0000*\u0000jtitle\";s:22:\"Fuzzy sets and systems\";s:9:\"\u0000*\u0000stitle\";s:15:\"Fuzzy sets syst\";s:7:\"\u0000*\u0000date\";s:4:\"2007\";s:9:\"\u0000*\u0000volume\";s:3:\"158\";s:8:\"\u0000*\u0000issue\";s:1:\"2\";s:8:\"\u0000*\u0000spage\";s:3:\"194\";s:8:\"\u0000*\u0000epage\";s:3:\"212\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0165-0114\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"CHUNSHIEN LI\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:1:{i:0;s:17:\"CHENG, Kuo-Hsiang\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"FSSYD8\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:8:\"\u0000*\u0000place\";s:9:\"Amsterdam\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:2:\"19\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Panist access
"O:12:\"IstexOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1016\/j.fss.2006.09.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:9:\"\u0000*\u0000jtitle\";s:22:\"Fuzzy sets and systems\";s:9:\"\u0000*\u0000stitle\";s:15:\"Fuzzy sets syst\";s:7:\"\u0000*\u0000date\";s:4:\"2007\";s:9:\"\u0000*\u0000volume\";s:3:\"158\";s:8:\"\u0000*\u0000issue\";s:1:\"2\";s:8:\"\u0000*\u0000spage\";s:3:\"194\";s:8:\"\u0000*\u0000epage\";s:3:\"212\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0165-0114\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"CHUNSHIEN LI\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:1:{i:0;s:17:\"CHENG, Kuo-Hsiang\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"FSSYD8\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:8:\"\u0000*\u0000place\";s:9:\"Amsterdam\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:2:\"19\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Istex access
"O:16:\"UnpaywallOpenUrl\":35:{s:8:\"\u0000*\u0000email\";s:27:\"assistance-portail@inist.fr\";s:6:\"\u0000*\u0000fmt\";N;s:6:\"\u0000*\u0000doi\";s:25:\"10.1016\/j.fss.2006.09.002\";s:6:\"\u0000*\u0000pii\";N;s:7:\"\u0000*\u0000pmid\";N;s:9:\"\u0000*\u0000atitle\";N;s:9:\"\u0000*\u0000jtitle\";N;s:9:\"\u0000*\u0000stitle\";N;s:7:\"\u0000*\u0000date\";N;s:9:\"\u0000*\u0000volume\";N;s:8:\"\u0000*\u0000issue\";N;s:8:\"\u0000*\u0000spage\";N;s:8:\"\u0000*\u0000epage\";N;s:8:\"\u0000*\u0000pages\";N;s:7:\"\u0000*\u0000issn\";N;s:8:\"\u0000*\u0000eissn\";N;s:9:\"\u0000*\u0000aulast\";N;s:10:\"\u0000*\u0000aufirst\";N;s:9:\"\u0000*\u0000auinit\";N;s:10:\"\u0000*\u0000auinitm\";N;s:5:\"\u0000*\u0000au\";N;s:9:\"\u0000*\u0000aucorp\";N;s:7:\"\u0000*\u0000isbn\";N;s:8:\"\u0000*\u0000coden\";N;s:8:\"\u0000*\u0000genre\";N;s:7:\"\u0000*\u0000part\";N;s:9:\"\u0000*\u0000btitle\";N;s:8:\"\u0000*\u0000title\";N;s:8:\"\u0000*\u0000place\";N;s:6:\"\u0000*\u0000pub\";N;s:10:\"\u0000*\u0000edition\";N;s:9:\"\u0000*\u0000tpages\";N;s:9:\"\u0000*\u0000series\";N;s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";N;}"
Unpaywall access
"O:16:\"EuropePMCOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1016\/j.fss.2006.09.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:9:\"\u0000*\u0000jtitle\";s:22:\"Fuzzy sets and systems\";s:9:\"\u0000*\u0000stitle\";s:15:\"Fuzzy sets syst\";s:7:\"\u0000*\u0000date\";s:4:\"2007\";s:9:\"\u0000*\u0000volume\";s:3:\"158\";s:8:\"\u0000*\u0000issue\";s:1:\"2\";s:8:\"\u0000*\u0000spage\";s:3:\"194\";s:8:\"\u0000*\u0000epage\";s:3:\"212\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0165-0114\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"CHUNSHIEN LI\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:1:{i:0;s:17:\"CHENG, Kuo-Hsiang\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"FSSYD8\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:8:\"\u0000*\u0000place\";s:9:\"Amsterdam\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:2:\"19\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Europe PubMed Central access
"O:11:\"BaseOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1016\/j.fss.2006.09.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:9:\"\u0000*\u0000jtitle\";s:22:\"Fuzzy sets and systems\";s:9:\"\u0000*\u0000stitle\";s:15:\"Fuzzy sets syst\";s:7:\"\u0000*\u0000date\";s:4:\"2007\";s:9:\"\u0000*\u0000volume\";s:3:\"158\";s:8:\"\u0000*\u0000issue\";s:1:\"2\";s:8:\"\u0000*\u0000spage\";s:3:\"194\";s:8:\"\u0000*\u0000epage\";s:3:\"212\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0165-0114\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"CHUNSHIEN LI\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:1:{i:0;s:17:\"CHENG, Kuo-Hsiang\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"FSSYD8\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:8:\"\u0000*\u0000place\";s:9:\"Amsterdam\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:2:\"19\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Base Search access
"O:12:\"ArXivOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:25:\"10.1016\/j.fss.2006.09.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:9:\"\u0000*\u0000jtitle\";s:22:\"Fuzzy sets and systems\";s:9:\"\u0000*\u0000stitle\";s:15:\"Fuzzy sets syst\";s:7:\"\u0000*\u0000date\";s:4:\"2007\";s:9:\"\u0000*\u0000volume\";s:3:\"158\";s:8:\"\u0000*\u0000issue\";s:1:\"2\";s:8:\"\u0000*\u0000spage\";s:3:\"194\";s:8:\"\u0000*\u0000epage\";s:3:\"212\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0165-0114\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:12:\"CHUNSHIEN LI\";s:10:\"\u0000*\u0000aufirst\";s:0:\"\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:1:{i:0;s:17:\"CHENG, Kuo-Hsiang\";}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:6:\"FSSYD8\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:0:\"\";s:8:\"\u0000*\u0000title\";s:74:\"Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling\";s:8:\"\u0000*\u0000place\";s:9:\"Amsterdam\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:2:\"19\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
arXiv access
