A Functional-Link based Interval Type-2 Compensatory Fuzzy Neural Network for Nonlinear System modeling

Jyh-Yeong Chang, Yang-Yin Lin, Ming-Feng Han, Chin-Teng Lin

研究成果: Conference contribution同行評審

12 引文 斯高帕斯(Scopus)

摘要

In this paper, the Functional-Link based Interval Type-2 Compensatory Fuzzy Neural Network (FLIT2CFNN) is a six-layer structure, which combines compensatory fuzzy reasoning method, and the consequent part is combined the proposed functional-link neural network with interval weights. The compensatory fuzzy reasoning method uses adaptive fuzzy operations of neuro-fuzzy systems that can make the fuzzy logic system more adaptive and effective. Initially, there is no rule in the FLIT2CFNN. A FLIT2CFNN is constructed using concurrent structure and parameter learning. The advantages of this learning algorithm are that it converges quickly and the obtained fuzzy rules are more precise. All of the antecedent part parameters and compensatory degree values are learned by gradient descent algorithm. Several simulation results show that the FLIT2CFNN achieves better performance than other feedforword type-1 and type-2 FNNs.
原文English
主出版物標題IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011)
發行者IEEE
頁面 939-943
頁數5
ISBN(列印)978-1-4244-7317-5
DOIs
出版狀態Published - 2010
事件2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
持續時間: 27 六月 201130 六月 2011

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

Conference

Conference2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
國家Taiwan
城市Taipei
期間27/06/1130/06/11

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