Simulated annealing based learning approach for the design of cascade architectures of fuzzy neural networks

Authors:
Chang-Wook Han;Jung-Il Park
Affiliations:
School of Electrical Engineering & Computer Science, Yeungnam University, Gyongbuk, South Korea;School of Electrical Engineering & Computer Science, Yeungnam University, Gyongbuk, South Korea
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

Citing 3
Cited 0

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Cascade Architectures of Fuzzy Neural Networks

Fuzzy Optimization and Decision Making

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Abstract

This paper is concerned with the optimization method of the cascade architectures of fuzzy neural networks. The structure of the network that deals with a selection of a subset of input variables and their distribution across the individual logic processors (LPs) is optimized with the use of genetic algorithms (GA). We discuss random signal-based learning employing simulated annealing (SARSL), a local search technique, aimed at further refinement of the connections of the neurons (GA-SARSL). A standard data set is discussed with respect to the performance of the constructed networks and their interpretability.