Wind Power Output Prediction with BP Neural Network Combining Genetic Algorithms

Xue Tao Pan; Ke Qing Qu

doi:10.4028/www.scientific.net/AMR.860-863.2526

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 860-863Wind Power Output Prediction with BP Neural...

Wind Power Output Prediction with BP Neural Network Combining Genetic Algorithms

Abstract:

While having been successfully applied in forecasting with many researches, back Propagation (BP) neural network are with problems such as permutation and premature convergence due to dependence on initial connection weights or other parameters. This paper investigates Genetic Algorithms (GA) evolved BP network and its application to wind power forecasting. Sample analysis with daily wind output data demonstrates that GA-based neural network is with better performance.

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Periodical:

Advanced Materials Research (Volumes 860-863)

Pages:

2526-2529

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.860-863.2526

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Online since:

December 2013

Authors:

Xue Tao Pan, Ke Qing Qu

Keywords:

BP Neural Network (BPNN), Forecasting, Genetic Algorithm (GA), Wind Power

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