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State-of-Art of Application of Artificial Neural Networks in Hydrology, Water Resources and Water Environment

Wang Dong(Hohai Univ, Nanjing, 210098)Cao Shengle(Shandong Univ. of Technology, Jinan, 250061 )  
At the beginning of this paper, the specific property of Artificial Neural Networks (ANN), aswell as the significance of its application in hydrology, water resources and water environment, are introducedbriefly. The state-of-the-art of the ANN application, such as forecasting, classifying, optimizating and so on,is evaluated in detail. The future study is also inquired as the remarks.
【Fund】: 山东省自然科学基金;;河海大学学生科技基金
【CateGory Index】: TV213
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Chinese Journal Full-text Database 10 Hits
1 CHEN Xi, WU Jinglu & WANG Ling ( Key Laboratory of Water Resources Development, Hohai University, Nanjing 210098 ,P. R. China) (Nanjing Institute of Geography and Limnology,CAS, Nanjing 210008 ,P. R. China);Prediction of Climate Change Impacts on Streamflow of Lake Bosten Using Artificial Neural Network Model[J];Journal of Lake Science;2005-03
2 ZUO Shu-hua(State key laboratory of estuarine and coastal research, East-china normal university, Shanghai 200062, China);State-of-art of Artificial Neural Networks in Analysis and Forecasting of Current and Sediment of China[J];Haihe Water Resources;2004-06
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4 XIAO Ying1,LI Zhen-xing2,DONG Yu-hua1(1.Dalian Nationality University,Dalian 116600,China;2.91550 Army 94 Unit,Dalian 116600,China);Research on Flood Forecast Based on Recursion Neural Network with Bias Unit[J];Journal of Luoyang University;2007-02
5 LI Rong,GUO Beiling (College of Civil and Hydraulic Engineering,Ningxia University,Yinchuan 750021,China);Artificial neutral networks application in relation analyzing of river high-water level and flow[J];Ningxia Engineering Technology;2009-02
6 HUANG Tian-qiang1,ZHUO Fei-bao1,YE Fei-yue2(1.Department of Computer Science,School of Mathematics & Computer Science,Fujian Normal University,Fuzhou 350007,China;2.Institute of Computer Science & Engineering,Jiangsu Teachers University of Tehcnology,Changzhou 213001,China);Environment Prediction Method Based on Spatial Autocorrelation[J];Journal of Qingdao University(Natural Science Edition);2007-04
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