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

유량 보간 신경망 모형의 개발 및 낙동강 유역에 적용

  • 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.)
  • 손아롱 (경북대학교 건설, 토목공학부) ;
  • 한건연 (경북대학교 건설, 토목공학부) ;
  • 김지은 (경북대학교 건설, 토목공학부)
  • Received : 2009.07.01
  • Accepted : 2009.09.22
  • Published : 2009.10.31

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

References

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