This paper used RBF artificial neural network to evaluate the underground water contaminated by the leachate of waste dump of open pit coal mine of Xinqiu in Fuxin. Firstly, with the advantages of neural network method in dealing with nonlinear problem, the RBF neural network model was built. Then, the normalized standard matrix was taken as training sample and the MATLAB software was used to train the training sample. Finally, the monitoring data were taken as test samples and were inputted in the RBF neural network model to evaluate the groundwater quality of study area. At the same time, the concept of degree of membership was adopted in the result making it more objective and accurate. The result shows that the ground water of this mining is seriously polluted, class of its pollution is Ⅳ-Ⅴ.The method with strong classification function and reliable evaluation results is simple and effective, and can be widely applied in all kinds of water resources comprehensive evaluation.
Remote sensing of chemical anomalies in the atmosphere in influence zone of Korkino open pit coal mine
