相关实验视频

基于贝叶斯优化时空集成和压缩深度残余网络的风速间隔预测

Yun Wu1, Yongzhen Gong2, Xiaoguo Chen3

  • 1College of Electrical and Information Engineering, Hunan University, Changsha 410082, China.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

一个新的空间时间集成和压缩深度残留 (STiCDRS) 模型提高了风速预测的准确性. STiCDRS-非参数核密度估计 (STiCDRS-NKDE) 混合模型为风电场规划提供可靠的概率预测.

关键词:
贝叶斯优化的贝叶斯优化预测NKDE间隔的预测剩余结构的残留结构时间卷积网络 时间卷积网络预测风速的预测

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