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Updated: Jan 29, 2026

Stress-Enhanced Fear Learning, a Robust Rodent Model of Post-Traumatic Stress Disorder
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一个混合联合学习框架,用于提高非侵入性负载监控中的隐私和稳定性

Jing Rong1, Qiuzhan Zhou1, Huinan Wu1

  • 1College of Communication Engineering, Jilin University, Changchun 130012, China.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
概括

本研究介绍了一种混合联合学习 (FL) 框架,用于智能电网中的非侵入性负载监控 (NILM). 它通过在集中和分散的FL模式之间动态切换来增强隐私和对攻击的稳定性.

关键词:
联合学习的联合学习模型的稳定性 模型的稳定性非侵入性负载监控 (NILM) 是一种非侵入性负载监控.保护隐私 保护隐私 保护隐私智能电网是先进的计量基础设施.

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