An approach for generation of perception frames based fuzzy neural network from data

Authors:
Aleksandar Milosavljevic;Leonid Stoimenov;Dejan Rančic
Affiliations:
Computer Science Department, Faculty of Electronic Engineering, University of Nis, Nis, Serbia;Computer Science Department, Faculty of Electronic Engineering, University of Nis, Nis, Serbia;Computer Science Department, Faculty of Electronic Engineering, University of Nis, Nis, Serbia
Venue:
WSEAS TRANSACTIONS on SYSTEMS
Year:
2008

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Abstract

In this paper we present an approach for generation and initialization of fuzzy neural networks (FNN) from data. Fuzzy neural networks are concept that integrates some features of the fuzzy logic and the artificial neural networks theory. Based on analysis of several different fuzzy neural networks models, uniform representation method is presented, and two basic types are identified: FNN based on perception frames, and FNN with independent rules. Presented algorithm supports generation of fuzzy neural network based on perception frames through following steps: clustering of a training set, identification of input variables perception frames, generation of rules using training set, and training for adaptation using gradient descent method.