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http://dx.doi.org/10.5391/JKIIS.2005.15.4.437

Web-Based Forecasting System for Flood Runoff with Neural Network  

Hang, Dong-Guk (충북대학교 컴퓨터공학과)
Jun, Kye-Won (삼척대학교 방재기술전문대학교)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.4, 2005 , pp. 437-442 More about this Journal
Abstract
The forecasting of flood runoff in the river is essential for flood control. The purpose of this study is to test a development of system for flood runoff forecasting using neural network model. For the flood events the tested rainfall and runoff data were the input to the input layer and the flood runoff data were used in the output layer To choose the forecasting model which would make up of runoff forecasting system properly, real-time runoff in the river when flood periods were forecasted by using the neural network model and the state-space model. A comparison of the results obtained by the two forecasting models indicated the superiority and reliability of the neural network model over the state-space model. The neural network model was modified to work in the Web and developed to be the basic model of the forecasting system for the flood runoff.
Keywords
Neural network; flood runoff; web-based; state space;
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