UM
A new fast-F-CONFIS training of fully-connected neuro-fuzzy inference system
Jing Wang1; Yuan-Yan Tang2; Long Chen2; C. L. Philip Chen3; Chao-Tian Chen4
2015-09-28
Conference NameInternational Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)
Source PublicationICCSS 2015 - Proceedings: 2015 International Conference on Informative and Cybernetics for Computational Social Systems
Pages99-104
Conference DateAUG 13-15, 2015
Conference PlaceChengdu, PEOPLES R CHINA
CountryCHINA
PublisherIEEE
Abstract

In this paper, Fuzzy Neural Network (FNN) is transformed into an equivalent Fully Connected Neuro-Fuzzy Inference System (F-CONFIS). The F-CONFIS is a new type of neural network that differs from traditional neural networks, which there are the dependent and repeated weights. For these special properties, its learning algorithm should be different from that of the conventional neural networks. Therefore, a new efficient training algorithm for F-CONFIS is proposed. Simulation examples are given to verify the validity of the proposed method, and achieve satisfactory results. In all engineering applications using FNN, developing Fast-F-CONFIS training has its emerging values.

KeywordConjugate Gradients Fuzzy Logic Fuzzy Neural Networks Gradient Descent Neural Networks
DOIhttps://doi.org/10.1109/ICCSS.2015.7281157
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Cybernetics ; Engineering, Electrical & Electronic
WOS IDWOS:000380436700020
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.School of Computer Science Guangdong polytechnic Normal University, China and Faculty of Science and Technology University of Macau, China
2.Department of Computer and Information Science Faculty of Science and Technology University of Macau, China
3.Department of Computer and Information Science Faculty of Science and Technology University of Macau, China
4.School of Computer Science Guangdong polytechnic Normal University, China
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Jing Wang,Yuan-Yan Tang,Long Chen,et al. A new fast-F-CONFIS training of fully-connected neuro-fuzzy inference system[C]:IEEE,2015:99-104.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Jing Wang]'s Articles
[Yuan-Yan Tang]'s Articles
[Long Chen]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jing Wang]'s Articles
[Yuan-Yan Tang]'s Articles
[Long Chen]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jing Wang]'s Articles
[Yuan-Yan Tang]'s Articles
[Long Chen]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.