摘要
运用BP人工神经网络模型的基本原理 ,根据流域产流产沙的基本规律 ,以流域降雨条件为基本影响因子 ,由流域实测资料建立了BP神经网络模型。该模型具有很好的学习和泛化性能。同时该模型能用于评价流域内人类活动因素对流域产流产沙规律的影响。将该模型应用于兴山、碧溪、顺利峡站 ,并与实测资料进行了分析比较 ,结果表明 ,模型基本合理。
Based on the basic principles of BP artificial neural network model and the fundamental law of water and sediment yield in a river basin,a BP artificial neural network model is developed by using observed data,with rainfall conditions serving as affecting factors.This model has satisfactory perfarmance of learning and generalization and can be also used to assess the influence of human activities on water and sediment yield in a river basin.The model is applied to compute the runoff and sediment transmission at Xingshan,Bixi and Shunlixia stations.Comparison between the results from the model and the observed data shows that the model is basically reasonable and reliable.
出处
《人民长江》
EI
北大核心
2000年第5期30-32,共3页
Yangtze River
基金
:国家"九五"三峡工程泥沙问题研究资助项目 !(编号 :95 -0 4-0 1-10 )
关键词
流域产流产沙
实测资料
BP神经网络模型
water and sediment yield in a river basin
observed data
water and sediment variation
BP neural network model
