Establishment and Application of Neuro-Fuzzy Flood Forecasting Model by Linking Takagi-Sugeno Inference with Neural Network (II) : Application and Verification

Takagi-Sugeno 추론기법과 신경망을 연계한 뉴로-퍼지 홍수예측 모형의 구축 및 적용 (II) : 실제 유역에 대한 적용 및 검증

  • 최승용 (국립방재연구소) ;
  • 한건연 (경북대학교 공과대학 건축.토목공학부)
  • Received : 2011.05.17
  • Accepted : 2011.06.13
  • Published : 2011.07.31


Based on optimal input data combination selected in the earlier study, Neuro-Fuzzy flood forecasting model linked Takagi-Sugeno fuzzy inference theory with neural network in Wangsukcheon and Gabcheon is established. The established model was applied to Wangsukcheon and Gabcheon and water levels for lead time of 0.5 hr, 1 hr, 1.5 hr, 2.0 hr, 2.5 hr, 3.0 hr are forecasted. For the verification of the model, the comparisons between forecasting floods and observation data are presented. The forecasted results have shown good agreements with observed data. Additionally to evaluate quantitatively for applicability of the model, various statistical errors such as Root Mean Square Error are calculated. As a result of the flood forecasting can be simulated successfully without large errors in all statistical error. This study can greatly contribute to the construction of a high accuracy flood information system that secure lead time in medium and small streams.


Supported by : 한국건설교통기술평가원


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