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Development of Flow Interpolation Model Using Neural Network and its Application in Nakdong River Basin  

Son, Ah Long (School of Archi. & Civil Engineering, Kyungpook National Univ.)
Han, Kun Yeon (School of Archi. & Civil Engineering, Kyungpook National Univ.)
Kim, Ji Eun (School of Archi. & Civil Engineering, Kyungpook National Univ.)
Publication Information
Journal of Environmental Impact Assessment / v.18, no.5, 2009 , pp. 271-280 More about this Journal
Abstract
The objective of this study is to develop a reliable flow forecasting model based on neural network algorithm in order to provide flow rate at stream sections without flow measurement in Nakdong river. Stream flow rate measured at 8-days interval by Nakdong river environment research center, daily upper dam discharge and precipitation data connecting upstream stage gauge were used in this development. Back propagation neural network and multi-layer with hidden layer that exists between input and output layer are used in model learning and constructing, respectively. Model calibration and verification is conducted based on observed data from 3 station in Nakdong river.
Keywords
FFN; flow interpolation; neural network; river flow estimation;
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