Artificial Neural Network (ANN) Method for Predicting of Hydrochemical Types of Salt Lakes

The prediction of hydrochemical types of salt lakes by probability artificial neural network model, which is one of the typical Radial basis function networks was studied. The good classing and predicting results were obtained. The average accuracy for predicting of hydrochemical types of salt lakes was 91.0%. Both the experimental results and structure analysis of neural networks indicated that the probability artificial neural network method is much better than the back-propagation (BP) neural network method . In fact, this study provides a new tool for chemical pattern recognition.