Comparison of the Extreme Learning Machine with the BP Neural Network for Short-Term Prediction of Wind Power

Abstract:

Extreme learning machine (ELM) is a new and effective single-hidden layer feed forward neural network learning algorithm. Extreme learning machine only needs to set the number of hidden layer nodes of the network, and there is no need to adjust the neural network input weights and the hidden units bias, and it generates the only optimum solution, so it has the advantage of fast learning and good generalization ability. And the back propagation (BP) neural network is the most maturely applied. This paper has introduced the extreme learning machine into the wind power prediction. By comparing the wind power prediction method using the BP neural network. Study shows that the extreme learning machine has better prediction accuracy and shorter model training time.

• Periodical: Advanced Materials Research (Volumes 608-609)
• Pages: 564-568
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.608-609.564
• Online since: December 2012
• Authors: Yi Hui Zhang, He Wang, Zhi Jian Hu, Meng Lin Zhang, Xiao Lu Gong, Cheng Xue Zhang
• Keywords: BP Neural Network (BPNN), Extreme Learning Machine, Wind Power, Wind Power Prediction

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