Markov model in proving the convergence of fuzzy genetic algorithm

Tran Manh Tuan, Le Ba Dung
Author affiliations

Authors

  • Tran Manh Tuan School of Information and Telecommunication, Thai Nguyen University, Viet Nam
  • Le Ba Dung Institute for Tropical Technology, VAST, 18 Hoang Quoc Viet, Cau Giay, Ha Noi, Viet Nam

DOI:

https://doi.org/10.15625/0866-708X/51/3/9587

Keywords:

genetic algorithm, fuzzy theory, fuzzy rules, neural network

Abstract

Genetic Algorithms (GA) was concerned by many authors and researchers from all over the world. There were results in different fields of our lives. But the convergence of GA is an open problems. In this paper, we propose a method using Markov model to prove the convergence of GA. At first, in section 2, we review fundamental concepts in Markov Model, then we present important role of Markov model in GA (section 3). After that, in section 4, we show the weak convergence of GA base on Markov model. In the end, in section 5, we also illustrate these using experiment results.

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Published

09-04-2017

How to Cite

[1]
T. Manh Tuan and L. Ba Dung, “Markov model in proving the convergence of fuzzy genetic algorithm”, Vietnam J. Sci. Technol., vol. 51, no. 3, pp. 267–277, Apr. 2017.

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Articles