数据挖掘技术在径流预报中的应用  

Application of Data Mining to Runoff Prediction

作　　者：李彩林[1] 许慧君[1] 王金文[1] 

机构地区：[1]华中科技大学水电与数字化工程学院

出　　处：《水电自动化与大坝监测》2007年第2期75-78,共4页HYDROPOWER AUTOMATION AND DAM MONITORING

摘　　要：介绍了基于数据挖掘技术的径流预报方法,建立了以人工神经网络(ANN)为挖掘工具的水文预报模型,利用反向传播(BP)模型进行挖掘工作,通过权系数修正提高收敛速度。结合工程项目进行了模型的实际预测,并与普通模型相比较。实测结果和分析说明,该模型有较好的预测精度,有实际应用价值。The data mining-based runoff prediction method is introduced, With the data-mining tool ANN, a runoff prediction model is built up. The BP model is used as the data-mining tool, and the convergence rate is improved with the modification of the weight coefficients. The model is tested in a project and compared with general models. The test result and analysis illustrate its good precision of prediction and good value of application,

关 键 词：径流预报 数据挖掘 人工神经网络 反向传播模型 

分 类 号：TV697.1[水利工程—水利水电工程] P338.2[天文地球—水文科学]