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BP神经网络在焉耆盆地农田排水量
引用本文:刘延锋,靳孟贵,曹英兰. BP神经网络在焉耆盆地农田排水量[J]. 中国农村水利水电, 2006, 0(1): 4-6
作者姓名:刘延锋  靳孟贵  曹英兰
作者单位:1. 中国科学院武汉岩土力学研究所,武汉,430071;中国地质大学环境学院,武汉,430074
2. 中国地质大学环境学院,武汉,430074
基金项目:高等学校博士学科点专项科研项目;中国科学院资助项目
摘    要:利用BP神经网络技术对焉耆盆地农田排水量进行预测。利用灰色关联度分析确定了排水量与各影响因素的关系,选取了对排水量影响最大的5个因素作为BP网络的输入,利用均匀设计方法,确定了最优的神经网络结构。估算结果表明利用BP神经网络可以准确的估算农田排水量,最大相对误差仅为-2.45%。

关 键 词:BP神经网络  均匀设计  灰色关联度  焉耆盆地
文章编号:1007-2284(2006)01-0004-03
收稿时间:2005-05-12
修稿时间:2005-05-12

Application of BP Neural Network in The Estimation of Farmland Drainage in Yanqi Basin
LIU Yan-feng,JIN Meng-gui,CAO Ying-lan. Application of BP Neural Network in The Estimation of Farmland Drainage in Yanqi Basin[J]. China Rural Water and Hydropower, 2006, 0(1): 4-6
Authors:LIU Yan-feng  JIN Meng-gui  CAO Ying-lan
Affiliation:1. Institute of Rock and Soil Mechanics, the Chinese Academy of Sciences, Wuhan 430071, Huhei, China; 2. School of Environmental Studies, China University of Geosciences, Wuhan 430074, Hubei, China
Abstract:BP neural network is used to estimate the farmland drainage in Yanqi Basin, Xinjiang Autonomous Region, China. The correlation between farm drainage and the influencing factors was estimated by gray correlation degree method. The five most important influencing factors were chosen to be the input for the BP neural network to estimate the farmland drainage. In order to obtain the optimal structure of BP neural network, the uniform design was employed. The results of estimation show that BP neural network can estimate farmland drainage accurately with the largest relative error only of 2.45G.
Keywords:BP neural network   uniform designs gray correlation degrees Yanqi Basin
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