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Deep-insights guided evolutionary algorithm for optimization
DOI:10.1016/j.eswa.2025.129538.png)
Abstract
En 中文
• 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.
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W

