Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Journal of Liaoning Technical University》 2004-02
Add to Favorite Get Latest Update

Forecast water consumption with improved BP neural network

MA Feng-hai1, YANG wei2 , YANG Fan 4,YU Xiao-xi 3 ( 1.Office of Discipline Construction , Liaoning Technical University,Fuxin 123000,China;2.Benxi Iron-steel Company, Benxi 117100, China;3. College of Civil and Architecture Engineering, Liaoning Technical University,Fuxin 123000,China;4. Dept. of Surveying Engineering, Liaoning Technical University,Fuxin 123000,China)  
Based on the characteristics of water consumption, the paper established the model to forecast water consumption with the improved BP neural network and applied genetic algorithms to optimize the weight matrix. The forecast result shows that the improved BP neural network is better than the one only using the Grey theory forecasting or BP neural network forecasting. The model is trained with the water consumption data of Benxi Iron-steel Company and used to forecast water consumption. Comparing the forecast results with the Grey theory forecasting and BP algorithm it is concluded that the improved BP neural network model has the small error in forecasting water consumption, at the same time it can overcome shortcomings of other algorithms.
【Fund】: 辽宁省教育厅攻关计划基金资助项目(202183392)
【CateGory Index】: TU991
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved