摘要
为了探索提高径流中长期预测精度的有效途径,尝试建立了基于支持向量机的径流预测模型,并应用于西江流域梧州站的年、月径流预测中,取得了很好的效果。并与神经网络预测进行对比,结果表明该模型的预测精度要高于人工神经网络模型。
To increase the efficiency of medium and long term runoff prediction, a prediction model based on support vector machine was recommended in this paper. The results show that the model has a good effect on forecasting the runoff in Xijiang basin. It is proven that the precision of SVM model is higher than that of neural network.
出处
《水电能源科学》
2006年第4期4-7,共4页
Water Resources and Power
基金
国家自然科学基金资助项目(50579009)
广西水利水电科技计划项目(桂水科合字(2005)2号)
关键词
径流预测
支持向量机
回归模型
runoff forecast
support vector machine
regression model
