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Open access 2026

Optimization of Artificial IntelligenceDriven Evolutionary Algorithms for Complex Engineering Problems

An evolutionary algorithm optimization framework (DLRL-EAF) that fuses deep learning and reinforcement learning is proposed that significantly reduces the time and resource costs of problem-solving in practical engineering applications and demonstrates its practical value in industrial settings.

P. Jia, F. Zhang · 0 citations

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