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A constrained multiobjective optimization coevolutionary algorithm with Wilcoxon-Bayesian for synchronous optimal pulsewidth modulation

delete2026-06-18
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PRE
AI
Q
Qian Shi
H
Heming Jia *
Y
Yongchao Li
M
Mahmoud Abdel-Salam
DOI：10.1016/j.asoc.2026.115783delete
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Abstract

Abstract

En 中文
• Wilcoxon test dynamically identifies problem types for adaptive search. • Bayesian resource allocation reduces dual-population computational costs. • WBCMO exhibits robust performance on complex SOPWM engineering instances.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

M
Mansoura University
Scholars:
7.6K
Papers: 6.0K
Citations: 1.1W
C
changchun university of technology
Scholars:
1.6K
Papers: 455
Citations: 0
H
Heilongjiang Bayi Agricultural University
Scholars:
3.5K
Papers: 1.4K
Citations: 1.7K
Sanming University cover
Sanming University
Scholars:
704
Papers: 492
Citations: 476
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