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Titlebook: Brain Storm Optimization Algorithms; Concepts, Principles Shi Cheng,Yuhui Shi Book 2019 Springer Nature Switzerland AG 2019 Computational I

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樓主: Autopsy
11#
發(fā)表于 2025-3-23 12:29:51 | 只看該作者
Brain Storm Algorithm Combined with Covariance Matrix Adaptation Evolution Strategy for Optimizationehavior. Meanwhile, the covariance matrix adaptive evolutionary strategy algorithm (CMA-ES) which belongs to the field of evolutionary strategy is also concerned. The purpose of this paper is to combine the search capability of BSO with the search efficiency of CMA-ES to achieve a relatively balanced and effective solution.
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發(fā)表于 2025-3-23 13:57:03 | 只看該作者
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發(fā)表于 2025-3-23 19:35:40 | 只看該作者
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發(fā)表于 2025-3-23 22:35:41 | 只看該作者
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發(fā)表于 2025-3-24 09:36:35 | 只看該作者
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發(fā)表于 2025-3-24 13:09:19 | 只看該作者
Lecture Notes in Computer Sciencetima of optimization problems. Hundreds of articles on the BSO algorithms have been published in different journals and conference proceedings, even though there are more questions than answers. In this chapter, BSO algorithms are comprehensively surveyed and the future research directions are discu
18#
發(fā)表于 2025-3-24 15:15:16 | 只看該作者
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發(fā)表于 2025-3-24 22:46:04 | 只看該作者
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發(fā)表于 2025-3-25 01:18:20 | 只看該作者
Lecture Notes in Computer Scienceronmental pollution. A novel Multi-objective Differential Brain Storm Optimization (MDBSO) algorithm is proposed to solve EED problem in this chapter. Different from the classical BSO, the clustering operation is designed in the objective space instead of solution space to improve the computing effi
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