| Title |
Application of Neural Network Model to the Real-time Forecasting of Water Quality |
| Authors |
조용진 ( Yong Jin Cho ) ; 연인성 ( In Sung Yeon ) ; 이재관 ( Jae Kwan Lee ) |
| Keywords |
Neural network; Discharge; Water quality; Real-time water quality monitoring |
| Abstract |
The objective of this study is to test the applicability of neural network models to forecast water quality at Naesa and Pyongchang river. Water quality data devided into rainy day and non-rainy day to find characteristics of them. The mean and maximum data of rainy day show higher than those of non-rainy day. And discharge correlate with TOC at Pyongchang river. Neural network model is trained to the correlation of discharge with water quality. As a result, it is convinced that the proposed neural network model can apply to the analysis of real time water quality monitoring. |