Water Environment Evaluation DSS Based On GIS

Neural Network has been widely used in many fields since it came into being. Now ft has been developed to be a useful nonlinear processing tool. Prediction is one of important application field of neural network. Since most of the general predicting methods have difficult in processing nonlinear cases. While neural network is competent for nonlinear processing for its excellent nonlinear character, predicting methods based on neural network extend the space of predicting research.Water resource is an important environment resource in realizing the persistence development. In the course of establish water environment model, we commonly take the main factors into account and neglect the subordinate factors in virtual of the complexity of water environment. It brings on many problems in water environment evaluation management.The followings are what this paper has done in prediction research especially water environment influence evaluation. This paper designed and realized all models in the water environment evaluation DSS based on GIS. It includes model base management subsystem; water environment actuality evaluation subsystem; water environment forecast analysis subsystem. After predigesting and realizing the water quality mathematic models, the neural network model is used to forecast the water environment influence; the genetic arithmetic is used to optimize the parameters and structure of neural network. Then system designing, interface development and model programming have been done.The result shows that neural network model is more precisely and convenient than water mathematic model. Genetic algorithm can choose the exact structure of model. It makes the neural network more quickly and efficiently.