Back propagation neural network with adaptive differential evolution algorithm for time series forecasting

作者：

Highlights：

• We propose a BPNN with adaptive differential evolution (ADE) for time series forecasting.

• ADE is used to search for global initial connection weights and thresholds of BPNN.

• The proposed ADE–BPNN is effective for improving forecasting accuracy.

摘要

•We propose a BPNN with adaptive differential evolution (ADE) for time series forecasting.•ADE is used to search for global initial connection weights and thresholds of BPNN.•The proposed ADE–BPNN is effective for improving forecasting accuracy.

论文关键词：Time series forecasting,Back propagation neural network,Differential evolution algorithm

论文评审过程：Available online 27 August 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.08.018