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Study on the Application of an Improved Intelligent Group Algorithm

by Fengjuan Wang

1 Qiqihar University, Qiqihar, 161006, China
2 Heilongjiang Province Collaborative Innovation Center for Intelligent Manufacturing Equipment Industrialization, Qiqihar, 161006, China

* Corresponding Author: Fengjuan Wang. Email: email

Intelligent Automation & Soft Computing 2020, 26(5), 1073-1080. https://doi.org/10.32604/iasc.2020.010138

Abstract

The Particle swarm optimization algorithm (PSO) and the simulated annealing algorithm (SA) are two well-known stochastic and intelligent methods used for optimization. Both methods have some shortcomings. On the basis of the shortcomings of PSO and SA, this paper offers an enhanced intelligent group algorithm on the basis of the roulette rule to improve the parameter velocity ν of (PSO) and the initial temperature of SA algorithm. This paper gives a detailed introduction to the principle and flow of the new algorithm and introduces the application status of the new algorithm.

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Cite This Article

APA Style
Wang, F. (2020). Study on the application of an improved intelligent group algorithm. Intelligent Automation & Soft Computing, 26(5), 1073-1080. https://doi.org/10.32604/iasc.2020.010138
Vancouver Style
Wang F. Study on the application of an improved intelligent group algorithm. Intell Automat Soft Comput . 2020;26(5):1073-1080 https://doi.org/10.32604/iasc.2020.010138
IEEE Style
F. Wang, “Study on the Application of an Improved Intelligent Group Algorithm,” Intell. Automat. Soft Comput. , vol. 26, no. 5, pp. 1073-1080, 2020. https://doi.org/10.32604/iasc.2020.010138



cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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