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投稿时间：2009-04-07
投稿时间：2009-04-07
中文摘要: 系统边际电价的影响因素复杂多变.构建了一种以小波函数作为核函数的最小二乘支持向量机算法模型,并成功预测了系统边际电价.算例仿真结果表明,该模型不仅具有良好的泛化能力,而且能有效地提高电价预测精度.
Abstract:Many options have influences on the decision of the system marginal price.As the wavelet has the property of time-frequency localization and is a powerful tool for arbitrary function approximation, an allowed support vector kernel function based on the wavelet is proposed.Simulation results demonstrate that this method has better generalization performance and prediction accuracy.
文章编号：20090322 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| ZHAO Xiao-li | School of Eledtric Power and Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China |
引用文本：
赵晓莉.基于小波最小二乘支持向量机模型的系统边际电价预测[J].上海电力大学学报,2009,25(3):284-287.
ZHAO Xiao-li.Marginal Price Forecasting Based on Wavelet Lesat Square Support Vector Machine[J].Journal of Shanghai University of Electric Power,2009,25(3):284-287.
赵晓莉.基于小波最小二乘支持向量机模型的系统边际电价预测[J].上海电力大学学报,2009,25(3):284-287.
ZHAO Xiao-li.Marginal Price Forecasting Based on Wavelet Lesat Square Support Vector Machine[J].Journal of Shanghai University of Electric Power,2009,25(3):284-287.