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Titlebook: Data Science; 10th International C Chengzhong Xu,Haiwei Pan,Zeguang Lu Conference proceedings 2024 The Editor(s) (if applicable) and The Au

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樓主: Orthosis
11#
發(fā)表于 2025-3-23 11:49:36 | 只看該作者
ex merging. Through training the DRL model, repetitive searches for vertex marking can be effectively avoided. Furthermore, the greedy algorithm can be augmented with genetic algorithms to address CCIP. Extensive experiments demonstrate the effectiveness of the proposed methods in addressing CCIP.
12#
發(fā)表于 2025-3-23 14:10:03 | 只看該作者
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發(fā)表于 2025-3-23 21:00:08 | 只看該作者
14#
發(fā)表于 2025-3-24 00:24:14 | 只看該作者
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發(fā)表于 2025-3-24 04:48:46 | 只看該作者
16#
發(fā)表于 2025-3-24 07:56:15 | 只看該作者
17#
發(fā)表于 2025-3-24 14:18:55 | 只看該作者
https://doi.org/10.1007/978-3-322-89670-4t is recommended that the legal system be further strengthened and that the "1?+?4" strategy of moderate and diversified economic development be implemented to promote high-quality economic development.
18#
發(fā)表于 2025-3-24 17:19:37 | 只看該作者
19#
發(fā)表于 2025-3-24 21:45:40 | 只看該作者
20#
發(fā)表于 2025-3-25 02:05:02 | 只看該作者
A Deep Reinforcement Learning Control Strategy with Integrated Droop Control for Parallel DC-DC Buckde control (SMC), the proposed strategy, leveraging the fast adaptive capability of DRL, significantly reduces the performance recovery time when disturbances occur. The simulation results illustrate the effectiveness of the approach in the presence of significant signal disturbances.
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