节点文献
基于非线性IRWLS-SVM短期电价预测的改进方法
Short Period Eelectricity Price Forecast Based on Nonlinear Irwls-svm Improved Method
【摘要】 本文提出了一种基于非线性IRWLS-SVM的短期电价预测的模型.首先对不同的损失函数进行仿真,选出具有一定鲁棒性的Huber损失函数来适应模型小的变化.然后比较线性、径向基、多项式3种核函数.仿真结果表明,多项式核函数的预测效果最好.最后提出了一种改进的非线性IRWLS-SVM算法,仿真结果表明改进后的算法提高了局部预测精度.
【Abstract】 This paper has introduced a short period electricity price forecast model based on nonlinear iterative re-weighted least squares(IRWLS) support vector machine(SVM).First of all,it has simulated with different cost functions;and the result has indicated that Huber cost function has robustness,and it can adapt to small changes of the model.Then,this paper has compared with three kernel functions,i.e.linear kernel function,radial basis kernel function and polynomial kernel function.The simulation results show that the polynomial one has the best regression result.At last,the paper proposes an improved algorithm which can improve the local forecasting precision.
【Key words】 support vector machine(SVM); nonlinearing; short period electricity price forecast;
- 【文献出处】 三峡大学学报(自然科学版) ,Journal of China Three Gorges University(Natural Sciences) , 编辑部邮箱 ,2012年06期
- 【分类号】TM715
- 【被引频次】2
- 【下载频次】65