My paper intends to build a model based on the application of artificial neural networks such as BP, RBF and non-linear method such as supportive vector machine in classifying the data on the same water quality. In such a process, using supportive vector machine, adopted radial basic function (RBF), methodologies such as normalization, dimension reduction, and grid search algorithm to get optimization out of relevant parameter to classify the water quality. the results of my experiment suggest that among non-linear methods, combining the use of supportive vector machine with the relevant pre-processing data methods has proved more accurate in the classification, thus making it worth further promotion