| Title |
Detecting Water Pollution Source based on 2D fluid Analysis in Virtual Channel |
| Authors |
연인성 ( In Sung Yeon ) ; 조용진 ( Yong Jin Cho ) |
| Keywords |
Backtracking; 2D model; Multi-perceptron; Water pollution source |
| Abstract |
2D pollutant transport model was applied to the simulation of contaminant transport in the channel. At first, two kinds of virtual channels having different slopes were designed. The distribution of contaminant, which flows from one of the three drainages to the main channel, was simulated by each 2D model. Concentrations of 745 nodes were converted to input data of neural network model (Multi-perceptron) for training and verification using matrix. The first three cases (Case A-1, A-2, A-3) were used for training Multi-perceptron, the other three cases (Case B-1, B-2, B-3) were used for verification. As a result, Multi-perceptron reasonably divided the cases into the three characteristics which have different contaminant distributions due to the different input point of water pollution source. It can be a useful methodology for the water quality monitoring and backtracking. |