Cascade-Correlation Algorithm을 이용한 증발접시 증발량의 모형화

Pan Evaporation Modeling using Cascade-Correlation Algorithm

Cascade-Correlation Neural Networks Model(CCNNM) is used to estimate daily evaporation using limited climatical variables such as atmospheric temperature, dewpoint temperature, relative humidity, wind speed, sunshine duration and radiation. DeBruln equation is applied to estimate daily free-surface evaporation. It is converted into pan evaporation using pan coefficient. The results of CCNNM shows better than those of Debruin equation. This research represents that the strong nonlinear relationship such as evaporation modeling can be generalized by the CCNNM ; a special type of Backpropagation algorithm Neural Networks Model.