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신경회로망을 이용한 Web기반 홍수유출 예측시스템

Web-Based Forecasting System for Flood Runoff with Neural Network

  • 황동국 (충북대학교 컴퓨터공학과) ;
  • 전계원 (삼척대학교 방재기술전문대학교)
  • 발행 : 2005.08.01

초록

하천에서의 홍수유출 예측은 하천의 치수적인 측면에서도 중요하다. 본 논문에서는 신경회로망 모형을 이용해서 개발된 홍수유출 예측 시스템의 적용성을 검토하였다. 입력층에는 강우자료와 홍수량 자료를 출력층에는 홍수유출량이 예측되도록 구성하였다. 홍수유출 예측 시스템 구성시 예측모형 선정을 위해 신경회로망 모형과 상태공간 모형을 이용하여 홍수시 실시간 하천유출량 예측을 수행하였다. 두 모형의 예측결과 비교시 신경회로망 모형이 실시간 홍수량 예측에 적합한 모형으로 선정되었다. 신경회로망 모형은 Web 상에서 사용이 가능하게 변환하여 홍수유출 예측시스템의 기본모형으로 개발하였다.

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.

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참고문헌

  1. N. Karunanithi, 'Neural Networks for River Flow Prediction,' Journal of Computing in Civil Engineering, ASCE Vol. 8, No. 2, pp. 201-219, 1994 https://doi.org/10.1061/(ASCE)0887-3801(1994)8:2(201)
  2. W. M. Anthony, 'Extened Rainfall-Runoff Modeling using Artificial Neural Networks,' Hydroinformatics '96, Proc. of the 2nd International Conf. on Hydro-informatics, Zurich, Switzerland, pp. 207-213, 1996
  3. J. C. Mason, R. K. Price and A. TEM'ME, 'A Neural Network Model of Rainfall-Runoff Using Radial Basis Functions,' Journal of Hydraulic Research, Vol. 34, No. 4, pp. 537-548, 1996
  4. M. N. French, W. F. Krajewski, and R. R. Cuykendall, 'Rainfall Forecasting in Space and Time using a Neural Network.' Journal of Hydrology, Vol. 137, pp. 1-31, 1992 https://doi.org/10.1016/0022-1694(92)90046-X
  5. Hsu, Kuo-Lin, H. V. Gupta and S. Sorooshian, 'Artificial Neural Network Modeling of the Rainfall-Runoff Process.' Water Resources Research, Vol. 3, pp. 2517-2530, 1995
  6. K. Thirumalaiah, 'River stage forecasting using Artificial Neural Networks', ASCE Journal of Hydrologic Engineering, Vol. 3, No. 1, pp. 26-32, 1998 https://doi.org/10.1061/(ASCE)1084-0699(1998)3:1(26)
  7. K. C. Shim, Spatial Decision Support System for Integrated River Basin Flood Control. Ph.D. Colorado State University, Fort Collins, CO, Spring, 1999
  8. Bin Zhang and Rao S. Govindaraju (2003). 'Geomorphology-based Artificial Neural Networks (GANNs) for Estimation of Direct Runoff over Watersheds.' Journal of Hydrology, Vol. 273, pp. 18-34 https://doi.org/10.1016/S0022-1694(02)00313-X
  9. J. S. R. Jang, C. T. Sun, and E. Mizutani, 'Neuro-Fuzzy and Soft Computing', Prentice Hall, pp. 198-331, 1997