Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)
- Volume 2 Issue 2
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- Pages.51-59
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- 1999
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- 1226-833X(pISSN)
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- 2765-5415(eISSN)
A Study on the Rainfall Forecasting Using Neural Network Model in Nakdong River Basin - A Comparison with Multivariate Model-
낙동강유역에서 신경망 모델을 이용한 강우예측에 관한 연구 - 다변량 모델과의 비교 -
- Cho, Hyeon-Kyeong (Dept. of Civil Eng., Yeungnam College of Science & Technology) ;
- Lee, Jeung-Seok (Dept. of Civil Eng., Kyungil University)
- Received : 1999.07.15
- Accepted : 1999.10.10
- Published : 1999.10.31
Abstract
This study aims at the development of the techniques for the rainfall forecasting in river basins by applying neural network theory and compared with results of Multivariate Model (MVM). This study forecasts rainfall and compares with a observed values in the San Chung gauging stations of Nakdong river basin for the rainfall forecasting of river basin by proposed Neural Network Model(NNM). For it, a multi-layer Neural Network is constructed to forecast rainfall. The neural network learns continuous-valued input and output data. The result of rainfall forecasting by the Neural Network Model is superior to the results of Multivariate Model for rainfall forecasting in the river basin. So I think that the Neural Network Model is able to be much more reliable in the rainfall forecasting.