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Deep-insights guided evolutionary algorithm for optimization
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AI
DOI：10.1016/j.eswa.2025.129538.png)
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Abstract
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• An insights-infused framework is proposed to assist EAs in optimization. • A coding method is developed to enable MLP networks handle varying data dimensions. • The framework utilizes neural networks to learn the evolutionary processes of EAs. • A self-evolution strategy is designed for net fine-tuning without external knowledge • The framework can solve different types of optimization problems.
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7.5
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3.0W
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10.2W
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