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ASME Press Select Proceedings

International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-China 2011), Volumes 1–3

By
Yi Xie
Yi Xie
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ISBN:
9780791859810
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011

Load forecasting is essential to the operation and plan of electric companies. To improve the accuracy of the load forecasting, a novel approach based PSO (particle swarm optimization) fuzzy v-Support vector machines is proposed in this paper for months electric load forecasting. PSO is used to optimize the parameters of the model. It considers the uncertain factors in load forecasting by fuzzy theory. The performance of the new model is evaluated with a typical region and compared with traditional support vector machines for regression. The experiment results demonstrate that the new method is more accurate than the traditional support vector regression.

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