Application Of Genetic Algorithm And BP Artificial Neural Network To Evaluation Of City System

City system is a typical immense system, and analysis, research, planning and management of city system should be performed in view of huge system. Evaluation of city system, which provides a scientific basis of planning, construction and management of city system, is a scientific method to understand and research city system.Regular evaluation methods are analyzed and studied in this paper. After their advantages, disadvantages and different application conditions are presented, it is concluded that these methods should be applied according to actual condition. First of all, projection pursuit algorithm is elaborated and analyzed, and is applied to evaluation of city system. Research results show that application of projection pursuit to evaluation of city system is feasible and effective. Genetic algorithm is a highly collateral, random, self-adaptive, general and globe search algorithm, which simulates biologic evolution process. In this paper, genetic algorithm is applied to optimizing the model optimum in what is evaluated by projection pursuit algorithm. Due to some problems of standard genetic algorithm, an improved genetic algorithm called disturbance genetic algorithm (DGA) is presented. According to the effect of DGA, this improved algorithm can deal with multiple hump function efficiently and achieve the global convergence with higher precision. Then artificial neural network, which is of memory function, can form the network model by training network according to expert knowledge and source data samples. What is mentioned above make it economical and easy to evaluate the same kind of problems by artificial neural network. Finally, the technique for order preference by similarity to solution based on genetic algorithm is also presented and applied, and its evaluation result is reasonable and practical.