(2302-7893) Improving the genetic algorithm in fuzzy cluster analysis for numerical data and its applications

Document Type : Research Paper

Authors

1 Faculty of Mechanical - Electrical and Computer Engineering, School of Technology, Van Lang University, Ho Chi Minh City, Vietnam

2 College of Natural Science, Can Tho University, Can Tho City, Vietnam

Abstract

This study proposes an automatic genetic algorithm in fuzzy cluster analysis for numerical data. In this algorithm, a
new measure called the FB index is used as the objective function of the genetic algorithm. In addition, the algorithm
not only determines the appropriate number of groups but also improves the steps of traditional genetic algorithm
as crossover, mutation and selection operators. The proposed algorithm is shown the step by step throughout the
numerical example, and can perform fast by the established Matlab procedure. The result from experiments show the
superiority of the proposed algorithm when it overcomes the existing algorithms. Moreover, it has been applied in
recognizing the image data, and building the fuzzy time series model. These show the potential of this study for many
real applications of the different fields.

Keywords

References

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Iranian Journal of Fuzzy Systems
Volume 20, Issue 5
September and October 2023
Pages 171-187

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