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A Self-trending Optimization Control Method for Power Network Communication Based on Graph Deep Reinforcement Learning
Column:Industrial Software and Industrial Large Models | 更新时间：2025-11-25

    • A Self-trending Optimization Control Method for Power Network Communication Based on Graph Deep Reinforcement Learning

    • “In the development of smart grids, power communication networks face challenges in real-time, reliability, and intelligence. Experts propose a self optimizing control strategy that integrates risk quantification and graph deep reinforcement learning to enhance the intelligence level of network management, strengthen network resilience, and respond to sudden communication failures. The simulation results show that the model performs excellently in bandwidth allocation efficiency and link fault recovery.”
    • Software Guide   Vol. 24, Issue 10, Pages: 56-64(2025)

    • DOI：10.11907/rjdk.251271    

      CLC： G642.0

    • Received：21 May 2025，

      Published：15 October 2025

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  • JIANG Yingjie,WEI Yongjing,SUN Chao,et al.A Self-trending Optimization Control Method for Power Network Communication Based on Graph Deep Reinforcement Learning[J].Software Guide,2025,24(10):56-64. DOI： 10.11907/rjdk.251271.

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