Support vector machines for wind speed prediction |
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| Authors: | M A Mohandes T O Halawani S Rehman Ahmed A Hussain |
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| Affiliation: | a Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia;b Center for Engineering Research, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia |
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| Abstract: | This paper introduces support vector machines (SVM), the latest neural network algorithm, to wind speed prediction and compares their performance with the multilayer perceptron (MLP) neural networks. Mean daily wind speed data from Madina city, Saudi Arabia, is used for building and testing both models. Results indicate that SVM compare favorably with the MLP model based on the root mean square errors between the actual and the predicted data. These results are confirmed for a system with order 1 to system with order 11. |
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| Keywords: | Author Keywords: Wind speed prediction Neural networks Multilayer perceptron Support vector machines |
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