基于改进ABC与LS-SVM算法的电力负荷预测的研究

为了解决电力负荷的非线性等问题和帮助电力企业迅速地制定电力的预计交易量,提出一种建立在最小二乘支持向量机算法基础上的电力负荷预测方法。采用改进的ABC算法优化惩罚因子C和核系数σ,再将最优解赋给LS-SVM用以预测。仿真结果证明:基于改进ABC与LS-SVM算法的电力负荷预测方法具有较高的预测精度,更小的误差,是一种有效的预测方法。

Research on prediction of electric power load based on improved ABC and LS-SVM algorithm

In order to solve problems such as nonlinear of power load and help electric power enterprise quickly formulate power expected volume of trade,a kind of method based on least squares support vector machine(LS-SVM) algorithm to forecast electric power load is proposed.Using improved ABC algorithm to optimize penalty factor C and nuclear factor σ,then the optimal solution can be assigned to LS-SVM to predict.The simulation results show that the method based on improved ABC and LS-SVM algorithm to forecast electric power load has high precision,less error,it is a kind of effective prediction method.