Physics-informed neural networks (PINNs) have shown remarkable prospects in solving forward and inverse problems involving ...
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Abstract: In the field of autonomous driving, safe and efficient decision-making through deep reinforcement learning remains a significant challenge. Existing methods often struggle to adapt to the ...
Best when Data density is irregular Domain-meaningful distance threshold exists KNN is preferable when data density varies across the feature space, and when a fixed, predictable neighborhood is ...
Abstract: With the rapid development of intelligent manufacturing technology, scheduling optimization of mechatronics assembly line has become a key issue to improve production efficiency and resource ...
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