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《JOURNAL OF HYDRAULIC ENGINEERING》 1998-10
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Neural networks for rainfall runoff modeling

Yang Rongfu\ Ding Jing\ Liu Guodong (Sichuan Union university)  
In this paper, two types of neural networks for rainfall runoff modeling are suggested: real outputs back feeding to input layer network(ROBIN) and additional output neuron back feeding input layer system (ADONIS). They are compared with HYMN(a hydrologically based neural network) and TANK(a lumped conceptual water buckets model). The results show that the proposed network models can reasonably simulate daily runoff series.
【Fund】: 国家自然科学基金
【CateGory Index】: TV121.1,TP18
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【Co-citations】
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1 GUO Chun-qing 1,TIAN Xi-zhao 1,2(1.College of Environmental Science and Engineering,Guilin University of Technology,Guilin 541004,China;2.Hebei Institute of Environmental Geology Exploration,Shijiazhuang 050021,China);A comprehensive forecast of water inflow in karst tunnels——Exemplified by the Zhujiayan karst tunnel[J];水文地质工程地质;2011-03
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【Co-references】
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