Probability density forecasting of wind power based on multi-core parallel quantile regression neural network

作者：

Highlights：

• This is a parallel quantile regression neural network wind power probability density forecasting model.

• The algorithm can improve the efficiency of quantile regression neural network.

• Results is evaluation by metrics of Speedup and Parallel efficiency.

摘要

•This is a parallel quantile regression neural network wind power probability density forecasting model.•The algorithm can improve the efficiency of quantile regression neural network.•Results is evaluation by metrics of Speedup and Parallel efficiency.

论文关键词：Parallel computing,Quantile regression neural network (QRNN),Master–slave model,Probability density forecasting,Wind power

论文评审过程：Received 16 April 2020, Revised 15 July 2020, Accepted 10 September 2020, Available online 19 September 2020, Version of Record 22 September 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.106431