灰色LS-SVM在中长期电力负荷预测中的应用

Fuwei Zhang, Wei Chen
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引用次数: 2

摘要

中长期负荷受多种因素影响,单一方法难以预测。本文分别分析了灰色预测方法和最小二乘支持向量机(LS-SVM)的优缺点,提出了一种新的灰色最小二乘支持向量机预测模型,该模型开发了灰色预测方法中积累生成的优点,减弱了原始序列中随机干扰因素的影响,增强了数据的正则性,避免了灰色预测模型中存在的理论缺陷。仿真结果表明,该模型具有良好的泛化能力和预测精度。关键词:中长期负荷预测;灰色模型;最小二乘支持向量机
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Grey LS-SVM in Mid and Long Term Power Load Forecasting
Mid-long term load is affected by many factors, it is difficult to forecast by a single method. This paper analyzes the advantages and disadvantages of grey forecasting method and least squares support vector machine (LS-SVM) respectively, proposes a new forecasting model of grey least squares support vector machine which develops the advantages of accumulation generation in the grey forecasting method, weakens the effect of stochastic disturbing factors in original sequence, strengthens the regularity of data and avoids theoretical defects existing in the grey forecasting model. The simulation results show that this model performs well in generalization ability and forecasting precision. Keywords-mid-long term load forecasting; grey model; least squares support vector machine
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