首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于BP神经网络的龙羊峡水库年末消落水位控制研究
引用本文:王义民,畅建霞,黄 强.基于BP神经网络的龙羊峡水库年末消落水位控制研究[J].西北农林科技大学学报(社会科学版),2005,33(7):68-72.
作者姓名:王义民  畅建霞  黄 强
作者单位:西安理工大学,水利水电学院,陕西,西安,710048
基金项目:国家自然科学基金项目(50479024),陕西省教育厅专项科研计划项目(04JK233)
摘    要:龙羊峡水库长期处于低水位运行,严重影响了其综合效益。运用逐步回归的方法寻找影响水库年末消落水位的主要因素,以此为基础,建立了控制龙羊峡水库年末消落水位的BP神经网络模型,并采用长系列资料对逐步回归模型和BP神经网络模型的预测结果进行了比较和误差分析。结果表明,BP神经网络模型优于逐步回归模型。

关 键 词:龙羊峡水库  年末消落水位  BP神经网络  水位控制  逐步回归
文章编号:1671-9387(2005)07-0068-05
收稿时间:2004/10/18 0:00:00
修稿时间:2004年10月18

Water level control of Longyangxia reservoir based on BP at the end of year
WANG Yi-min,CHANG Jian-xia,HUANG Qiang,XUE Xiao-jie,YU Chang-sheng,XI Qiu-yi.Water level control of Longyangxia reservoir based on BP at the end of year[J].Journal of Northwest Sci-Tech Univ of Agr and,2005,33(7):68-72.
Authors:WANG Yi-min  CHANG Jian-xia  HUANG Qiang  XUE Xiao-jie  YU Chang-sheng  XI Qiu-yi
Institution:(College of Water Resource and Hydroelectricity Engineering,Xi’an University of Technology,Xi’an,Shaanxi 710048,China)
Abstract:The Longyangxia reservoir has been operating at a low water level for a long time,which has affected the benefits of Longyangxia.In this paper,the main factors related to water level at the end of year of Longyangxia reservoir are discussed by using regress method.The BP model is also introduced for controlling Longyangxia reservoir water level.The prediction results are compared and analyzed between regress model and BP model.Results indicate that the BP model is more reasonable and feasible.
Keywords:Longyangxia reservoir  water level at the end of year  back propagation network  water level control  regress analysis
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《西北农林科技大学学报(社会科学版)》浏览原始摘要信息
点击此处可从《西北农林科技大学学报(社会科学版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号