Differential evolution and quantum-inquired differential evolution for evolving Takagi-Sugeno fuzzy models

Authors:
Haijun Su;Yupu Yang
Affiliations:
Department of Automation, Shanghai Jiaotong University, Shanghai 200240, PR China;Department of Automation, Shanghai Jiaotong University, Shanghai 200240, PR China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 13
Cited 1

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Abstract

The differential evolution (DE) is a global optimization algorithm to solve numerical optimization problems. Recently the quantum-inquired differential evolution (QDE) has been proposed for binary optimization. This paper proposes DE/QDE to learn the Takagi-Sugeno (T-S) fuzzy model. DE/QDE can simultaneously optimize the structure and the parameters of the model. Moreover a new encoding scheme is given to allow DE/QDE to be easily performed. The two benchmark problems are used to validate the performance of DE/QDE. Compared to some existing methods, DE/QDE shows the competitive performance in terms of accuracy.