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A noisy multi-objective evolutionary optimization algorithm based on Elman neural network

delete2025-09-06
delete0
PRE
AI
J
Jianxia Li
R
Ruochen Liu *
W
Wanfeng Chen
W
Weibin Li
DOI：10.1016/j.asoc.2025.113842delete
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摘要

摘要

En 中文
• E-NSGA-II 是一种尝试利用 Elman 神经网络求解 NMOPs 的方法。 • E-NSGA-II 采用自适应性建模来决定是否需要构建 Elman 网络。 • 混合选择解策略选择个体以增强多样性。 • 噪声驱动的采样调整采样次数以提升精度并降低成本。

期刊

Applied Soft Computing 封面图
Applied Soft Computing
IF:
6.6
论文数:
1.4W
被引数:
4.8W

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