HEC-5와 신경망을 이용한 댐운영의 최적화 = Optimization of Reservoir Operation using HEC-5 and Neural Network

다국어 초록 (Multilingual Abstract)

This study. which chose Sum-Jin river dam and Ju-Amdam of Sum-Jin river water system for objection region, forecasted inflow of dam to manage a multipurpose dam during flood period, using neural network model, executed HEC-5 to be inputted the foresaw and measured inflow data and investigated the result data. HEC-5 is dam imitative operating program. When no damaging channel capacity was 100% or 70%, this study investigated the flood control storage probability so that we understand concerning with no damaging channel capacity and the flood control storage capacity of reservoir.
As a result that forecasted dam inflow through neural network model, we got excellent forecasting outcome that the coefficient of determination is over 0.9. and find to be able to apply HEC-5 because. as a result that ￡ was applied to HCE-5 forecasting outcome and surveyed inflow data. the forecasting outcome were more superior managing result than real outflow one at the phases of peak flow control rate, reservoir outflow rate, and reswyoir storage rate. finally this study investigated abut application of HEC5 model at the best suited dam management and regulation of no damaging channel capacity. as deciding the best suited outflow by adjusting no damaging channel capacity.