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Titlebook: Advances in Swarm Intelligence; 14th International C Ying Tan,Yuhui Shi,Wenjian Luo Conference proceedings 2023 The Editor(s) (if applicabl

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期刊全称Advances in Swarm Intelligence
期刊简称14th International C
影响因子2023Ying Tan,Yuhui Shi,Wenjian Luo
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advances in Swarm Intelligence; 14th International C Ying Tan,Yuhui Shi,Wenjian Luo Conference proceedings 2023 The Editor(s) (if applicabl
影响因子This two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14.th. International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence”..The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the first part cover topics such as: Swarm Intelligence Computing; Swarm Intelligence Optimization Algorithms; Particle Swarm Optimization Algorithms; Genetic Algorithms; Optimization Computing Algorithms; Neural Network Search & Large-Scale Optimization; Multi-objective Optimization..
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The FLATCON System from Concentrix Solar,roved. However, there is still the risk of falling into the local optimal dilemma. Therefore, the change of population diversity is considered in the evaluation index of population status in this study. In order to further increase the activity of the global search range, the computational individua
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Terrestrial Concentrator PV Systems,ults show that the HAEO algorithm is more competitive than the existing algorithms in terms of accuracy and reliability. Therefore, HAEO can be considered an effective PV model parameter identification method.
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III-V Heterostructures in Photovoltaics,search space and the number of substrings of the chunks and double chunks of the message digest in the reference list matching with the incoming ssDeep digest is found and the similarity between the files is computed. It is shown that HHACOS algorithm scales well compared to the existing approaches
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