首页 | 本学科首页   官方微博 | 高级检索  
     

基于改进BP神经网络模型的苏帕河流域梯级电站水质综合评价
引用本文:王晓玲,段文泉,黄宁,陈夺峰,杨键.基于改进BP神经网络模型的苏帕河流域梯级电站水质综合评价[J].水利水电技术,2005,36(7):15-18.
作者姓名:王晓玲  段文泉  黄宁  陈夺峰  杨键
作者单位:1. 天津大学,环境科学与工程学院,天津,300072
2. 云南省地方电力投资有限公司,云南,昆明,650021
基金项目:天津市自然科学基金项目(043605611).
摘    要:引入人工神经网络(ANN)理论,提出了水环境质量综合评价的改进BP神经网络模型,并编制了相应的程序。将模型运用于苏帕河流域梯级电站水质综合评价中,结果表明改进的BP神经网络模型通过变步长法和加入动量项的方法不仅可以减少训练的次数,避免网络训练陷入平坦区,还可以提高网络的精度,减小全局误差。与传统评价方法相比,本模型全面考虑多种因素,评价结果更为客观、合理;相应所开发的评价系统适应性强,通用性好,简单易用,具有优越性。

关 键 词:水质综合评价  改进BP神经网络模型  苏帕河流域  梯级电站
文章编号:1000-0860(2005)07-0015-04
收稿时间:01 20 2005 12:00AM
修稿时间:2005年1月20日

Comprehensive evaluation on water quality for cascade hydropower stations in Supa River basin based on improved BP neural networks model
WANG Xiao-ling,DUAN Wen-quan,HUANG Ning,CHEN Duo-feng,YANG Jian.Comprehensive evaluation on water quality for cascade hydropower stations in Supa River basin based on improved BP neural networks model[J].Water Resources and Hydropower Engineering,2005,36(7):15-18.
Authors:WANG Xiao-ling  DUAN Wen-quan  HUANG Ning  CHEN Duo-feng  YANG Jian
Abstract:An improved BP neural networks model is introduced for evaluating the water quality comprehensively,and then the corresponding program is worked out herein. This model is applied to analyze the water quality for the cascade hydropower stations in Supa river basin. The results show that the improved model can speed up the convergence, avoid the flat region and improve the performance by changing the step length and adding the momentum item; which demonstrate that the suitability,feasibility and reasonability of the procedure can be ensured as well.
Keywords:comprehensive evaluation on water quality  improved BP neural networks model  Supa River basin  cascade hydropower stations
本文献已被 CNKI 维普 万方数据 等数据库收录!
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