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

•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. The back propagation neural network (BPNN) can easily...

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Veröffentlicht in:	Expert systems with applications Jg. 42; H. 2; S. 855 - 863
Hauptverfasser:	Wang, Lin, Zeng, Yi, Chen, Tao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.02.2015
Schlagworte:	Adaptive algorithms Artificial neural networks Back propagation Back propagation neural network Differential evolution algorithm Forecasting Mathematical models Neural networks Searching Thresholds Time series forecasting Time series forecasting Back propagation neural network Differential evolution algorithm
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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