Dual-Population Social Group Optimization Algorithm Based on Human Social Group Behavior Law

Bibliographic Data

ID22107382
AuthorsChao Wang (0000-0002-4737-0717, University of Electronic Science and Technology of China), Xianqi Zhang (0000-0002-0887-6192, Harbin Engineering University), Yi Niu (0000-0002-3806-0354, University of Electronic Science and Technology of China), Shan Gao (0000-0001-7424-476X, Harbin Engineering University), Jing Jiang (0000-0002-8912-3896, University of Electronic Science and Technology of China), Zezhan Zhang (0000-0002-5622-894X, University of Electronic Science and Technology of China), Peifeng Yu (0000-0002-7007-5986, University of Electronic Science and Technology of China), Hairong Dong (0000-0003-4369-3401, Beijing Jiaotong University)
Year2023
Volume10
Issue1
Pages166-177
Publication date2023-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2022.3141114
OpenAlexW4206763573
LanguageEN
References cited37

Inspired by the behavior law of human social groups, a new swarm intelligence algorithm named the dual-population social group optimization (DPSGO) algorithm is proposed in this article. Based on the primitive social group optimization (SGO) algorithm, dual-population grouping technology, reverse learning technology, immigration migration technology, and Gaussian mutation are introduced to further simulate the behavior law of actual human social groups. Experimental results and performance comparison show that the DPSGO algorithm has a better searchability and convergence rate. In addition, aiming at the socially hot issue of aviation safety, the simulation and experimental results show that the temperature measurement error can be reduced to less than 7.5 °C by using the DPSGO algorithm combined with reflected radiation correction to process the aeroengine multispectral radiation temperature measurement data. This article is of great significance to the design and optimization of swarm intelligence algorithms by using the behavior law of human social groups and provides valuable guidance for enhancing the safety monitoring of aeroengines

Algorithm · Economics · Mathematical optimization · Particle swarm optimization · Political science · Population · Sociology · Swarm intelligence · Advanced Multi-Objective Optimization Algorithms · Computer Science · Evacuation and Crowd Dynamics · Law · Mathematics · Metaheuristic Optimization Algorithms Research · Artificial Intelligence

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