研究论文

基于最小二乘支持向量机的风速组合预测模型

  • 周腊吾;陈静;戴浪
展开
  • 湖南大学电气与信息工程学院,长沙 410082

收稿日期: 2010-12-24

  修回日期: 2011-02-10

  网络出版日期: 2011-03-08

Wind Speed Combination Forecasting Model Based on Least Square Support Vector Machine

Expand

Received date: 2010-12-24

  Revised date: 2011-02-10

  Online published: 2011-03-08

摘要

探讨了基于最小二乘支持向量机的组合预测模型在风速短期预测中的可行性。该模型以BP神经网络、RBF神经网络、粒子群BP神经网络3种预测模型的风速预测值作为组合预测模型的输入,实际风速值为输出,利用最小二乘支持向量机回归算法构造风速间的非线性关系,以实现风速多步预测。将该模型的预测性能与BP神经网络组合预测模型、线性组合预测模型进行比较,通过平均绝对误差、误差平方和、平均相对误差3个指标进行评价。结果表明,最小二乘支持向量机预测模型的平均相对误差低于6%,其他误差指标也明显低于其他预测模型。因此,最小二乘支持向量机组合预测模型预测精度不仅高于任一单项预测模型预测精度,而且高于传统的线性组合预测模型与一般BP神经网络组合预测模型。验证了该模型在风速预测中的可行性。

本文引用格式

周腊吾;陈静;戴浪 . 基于最小二乘支持向量机的风速组合预测模型[J]. 科技导报, 2011 , 29(11-07) : 66 -68 . DOI: 10.3981/j.issn.1000-7857.2011.08.012

Abstract

In order to study the feasibility of combination forecasting model based on least squares support vector machine for wind speed short-term forecasting, the forecasting data coming from Back Propagation (BP) neural network, Radial Basis Function (RBF) neural network, and Particle Swarm Optimization neural network (PSOBP) were used as inputs and the actual wind speed was used as output in this model. The least squares support vector regression algorithm is used for constructing the nonlinear relationship in order to achieve multi-step forecasting for wind speed. The forecasting performance of the model is compared with BP combination forecasting model and linear combination forecasting model, and it was evaluated by mean absolute error, sum of squared error, and average relative error. The results indicate that the average relative error for least squares support vector machine prediction model is less than 6%; and the rest of error indicators for it are significantly lower than other models. Therefore its forecasting accuracy is not only better than any other single forecasting model, but also better than the traditional linear combination forecasting model. It validates the feasibility of least squares support vector machine combined forecasting model for wind speed forecasting.
文章导航

/