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Title |
Performance Evaluation of Short Term Wind Speed Prediction Techniques |
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Author |
K. Sreelakshmi, P. Ramakanth Kumar |
| Citation |
Vol. 8 No. 8 pp. 162-169 |
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Abstract |
Wind speed prediction from past observations has applications in many diverse fields such as Target tracking, Missile guidance, Satellite launch, Air traffic control, Weather forecasting, Ship navigation, Electrical power generation using wind energy. The wind speed is determined by many other atmospheric variables, such as pressure, moisture content, humidity, rainfall etc. Literature reports a number of models for wind speed prediction. In this paper a comparison is carried out between Neural network models and Support Vector Machine models built for predicting wind speed in short term. Analysis shows that SVM models compute faster & give better accuracies than the Neural Network models. |
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Keywords |
Short term wind speed prediction, Neural networks, Back propagation, Support Vector Machine [SVM], forecasting, hyper plane, kernels, classification |
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