標題: A Functional-Link based Interval Type-2 Compensatory Fuzzy Neural Network for Nonlinear System modeling
作者: Chang, Jyh-Yeong
Lin, Yang-Yin
Han, Ming-Feng
Lin, Chin-Teng
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: type-2 fuzzy systems;compensatory operation;structure learning;on-line fuzzy clustering
公開日期: 2011
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.
URI: http://hdl.handle.net/11536/14584
ISBN: 978-1-4244-7317-5
ISSN: 1098-7584
期刊: IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011)
起始頁: 939
結束頁: 943
顯示於類別:會議論文