改进RBF网络在短期负荷预测中的应用

2011 IEEE 2nd International Conference on Software Engineering and Service Science Pub Date : 2011-07-15 DOI:10.1109/ICSESS.2011.5982477

Niu Dong-xiao, Ji Ling, Tian Jie

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引用次数: 5

摘要

本文从短期负荷预测的实际应用出发，介绍了径向基函数网络，并利用最近邻聚类算法确定径向基函数的宽度，选择聚类中心和权值。预测结果表明，该方法具有较快的速度和较高的精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Improved RBF network applied to short-term load forecasting

From the practical application of short-term load forecasting, this article introduced the radial basis function network and use nearest neighbor clustering algorithm to determine the width of radial basis function, select the cluster centers and weights. The predicted results show that the method is faster and has higher precision.

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来源期刊

2011 IEEE 2nd International Conference on Software Engineering and Service Science

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