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Rank-driven salp swarm algorithm with orthogonal opposition-based learning for global optimization.

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第一作者： Zongshan,Wang

第一单位： School of Information Science and Engineering, Yunnan University, Kunming, 650500 China.

作者： Zongshan,Wang ^[1] ; Hongwei,Ding ^[1] ; Zhijun,Yang ^[2] ; Bo,Li ^[1] ; Zheng,Guan ^[1] ; Liyong,Bao ^[1]

作者单位： School of Information Science and Engineering, Yunnan University, Kunming, 650500 China. ^[1] School of Information Science and Engineering, Yunnan University, Kunming, 650500 China.;Yunnan Education Department, Kunming, 650500 China. ^[2]

关键词 Dynamic learning Engineering design optimization Global optimization Lens opposition-based learning Orthogonal experiment design Parameter extraction Photovoltaic models Robot path planning Salp swarm algorithm

DOI 10.1007/s10489-021-02776-7

PMID 34764621

发布时间 2022-07-16

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Applied intelligence (Dordrecht, Netherlands)

2022年52卷7期

7922-7964页

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Applied intelligence (Dordrecht, Netherlands)

2022年52卷7期

7922-7964页

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Rank-driven salp swarm algorithm with orthogonal opposition-based learning for global optimization.

Applied intelligence (Dordrecht, Netherlands)

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Rank-driven salp swarm algorithm with orthogonal opposition-based learning for global optimization.

Applied intelligence (Dordrecht, Netherlands)

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Applied intelligence (Dordrecht, Netherlands)

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