A recurrent self-organizing neural fuzzy inference network

Author

Juang, Chia-Feng ; Lin, Chin-Teng

Author_Institution

Dept. of Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

Volume

3

fYear

1997

fDate

1-5 Jul 1997

Firstpage

1369

Abstract

A recurrent self-organizing neural fuzzy inference network (RSONFIN) is proposed in this paper. The RSONFIN is constructed from a series of dynamic fuzzy rules. The temporal relations embedded in the network are built by adding some feedback connections representing the memory elements to a feedforward neural fuzzy network. Each weight as well as node in the RSONFIN has its own meaning and represents a special element in a fuzzy rule. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially in the RSONFIN. They are created online via concurrent structure identification (the construction of dynamic fuzzy if-then rules) and parameter identification (the tuning of the free parameters of membership functions). The structure learning together with the parameter learning forms a fast learning algorithm for building a small, yet powerful, dynamic neural fuzzy network. Simulations on temporal problems are performed

Keywords

feedforward neural nets; fuzzy neural nets; identification; inference mechanisms; learning (artificial intelligence); recurrent neural nets; self-organising feature maps; dynamic fuzzy rules; feedforward neural network; fuzzy reasoning; neural fuzzy inference network; parameter identification; parameter learning; recurrent neural network; self-organizing neural network; structure learning; Buildings; Control engineering; Feedforward neural networks; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Neural networks; Neurofeedback; Problem-solving; Recurrent neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on

Conference_Location

Barcelona

Print_ISBN

0-7803-3796-4

Type

conf

DOI

10.1109/FUZZY.1997.619743

Filename

619743