Fault Indicator Configuration Optimization Based on Cooperative Game Particle Swarm Algorithm

Authors

Xu Wang, College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaFollow
Weidong Ji, College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaFollow
Guohui Zhou, College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China

Abstract

In order to balance the reliability and economy of distribution network fault indicator, a multispace cooperative game particle swarm optimization algorithm is proposed. Based on the idea of population space grouping, the population activity space is adaptively divided, the particle game evolution in subspace is achieved, and the game calculation of particle fusion cosine similar reverse strategy is carried out, which well balances the convergence and diversity of the algorithm. The simulation results show that the adaptive multi-space division of population is conducive to jumping out of the local extreme value, and the game calculation integrating cosine similar reverse is conducive to improving the precision of population convergence. The method has good universality and effectiveness.

Recommended Citation

Wang, Xu; Ji, Weidong; and Zhou, Guohui (2023) "Fault Indicator Configuration Optimization Based on Cooperative Game Particle Swarm Algorithm," Journal of System Simulation: Vol. 35: Iss. 6, Article 13.
DOI: 10.16182/j.issn1004731x.joss.22-0192
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss6/13

First Page

1278

Revised Date

2022-04-13

DOI Link

http://dx.doi.org/10.16182/j.issn1004731x.joss.22-0192

Last Page

1289

CLC

TP301.6

Recommended Citation

Wang Xu, Ji Weidong, Zhou Guohui. Fault Indicator Configuration Optimization Based on Cooperative Game Particle Swarm Algorithm[J]. Journal of System Simulation, 2023, 35(6): 1278-1289.

DOI

10.16182/j.issn1004731x.joss.22-0192