基于人工神经网络的长江三峡年最大洪峰流量长期预报  

Long-term Prediction of Annual Maximum Peak Discharge at Yangtze Three Gorges Based on Artificial Neural Network

作　　者：孙树青[1] 胡国华[1] 左利芳[1] 

机构地区：[1]长沙理工大学河海工程学院,湖南长沙410076

出　　处：《水电能源科学》2007年第1期4-7,共4页Water Resources and Power

基　　金：湖南省自然科学基金资助项目(06JJ20027)

摘　　要：将统计相关性分析与模糊方法相结合,识别出影响宜昌站年最大洪峰流量的前期流域降水、大气环流形势等预报因子。比较了LMBP算法、自适应BP算法、变步长BP算法、加动量BP算法等几种常见改进BP算法的优缺点,探讨了BP网络建模过程中存在的问题,建立了LMBP算法和自适应BP算法相耦合的中长期水文预报模型。预报实践表明,所建模型合理、预报效果好、精度高、具有较高的推广和应用价值。An artificial neural network medium and long-term hydrological forecasting model combining with LM algorithm and self-adaptive algorithm was established in combining statistical analysis with fuzzy analysis, choosing predictors such as rainfall and atmospheric circulation in earlier stage which effect the annual maximum peak discharge at Yichang Station of Yangtze River, considering of comparing the advantage and disadvantage of several modified BP algorithms, discussing several problems in the modelling process. The result of calculation shows that the models are highly effective and are worth popularization and application.

关 键 词：LMBP算法 自适应BP算法 年最大洪峰 长期预报 

分 类 号：TV12[水利工程—水文学及水资源] TP183[自动化与计算机技术—控制理论与控制工程]