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-  2018 

基于粒子群优化支持向量机的短期负荷预测 Research on short term load forecasting based on particle swarm optimization-support vector machine

Keywords: 支持向量机,负荷预测,粒子群优化算法,最小二乘

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Abstract:

随着我国电力行业体制改革的不断深入,对负荷预测精度的要求也不断提高.为提高短期负荷预测的精度,针对单一核函数最小二乘支持向量机(LS-SVM)模型在实际使用中的问题,将高斯(RBF)核函数与多项式(Poly)核函数进行组合,得到了新的混合核函数,从而提高了SVM模型的学习能力与泛化能力;采用基于双种群的粒子群算法(DP-PSO)寻求混合核函数LS-SVM模型的最优参数;结合实际电网进行日平均负荷预测,算例结果表明,采用该负荷预测模型的平均误差仅为1.22%,预测精度较高

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