Application And Research Of Grey Clustering On Estimation Of City Competitiveness

The 21st century is the century of cities, during which the city's situation and role is more important in the development of economic society. How to improve the city's competitiveness and speed up its modern development has become a question which is generally concerned by many scholars. The quantified analysis of the competitiveness between different cities may help the leaders understand their position and situation, advantages and disadvantages clearly, grasp the key points that improve the city's competitiveness.Our country's dimensionality is so expansive that only our mainland has more than six hundred cities now. The evaluation index system is so huge that it's very hard to analyze all the cities one by one. By using the clustering analysis algorithm of the multi statistic analysis to analyze the complex city index data, we can get every city's remarkable individuality and common character in their competition ability, so that we can establish contraposing competition strategies. But,the research of our cities'competitiveness still at the stage of exploration, and our prior knowledge and experience are not enough. While the clustering analysis algorithm that we have needs that knowledge and experience in advance to setup the parameters during the statistic, which makes this algorithm be of a kind of limitation in the evaluation of cities'competition.So this paper proposes a brand-new grey clustering analysis algorithm and fully defines its mathematic model in order to make up the insufficiency of the existence one. It needn't confirm parameter artificially and avoids artificial effect to clustering result effectively; deal with the abnormal data efficiently, improves its anti-jamming ability; without limitation to the inputted sequence of the stylebook. The result of grey clustering analysis algorithm is more objective and accurate. The paper uses the object-oriented program principle and tools for the system to achieve, and carries out a large number of experiments, experimental results demonstrate validity of grey clustering analysis algorithm.Focusing on studying the more important factors to cities'competitiveness like transportation and education of the selected 200 important above-region sample cities, the paper applied the grey clustering analysis algorithm to the evaluation. Through detailed analysis to the clustering result, the test finally shows there are close relationship among economic development, transportation and education. Also, the economy is the key standard to measure a city's competitiveness. Therefore, the energetically development of transportation and education is the way to improve a city's competitiveness. The paper's research is based on the multi statistic analysis theory and combines qualitative analysis with quantitative analysis. On a certain scale it provides theoretical basis to relevant departments in charge of planning, programming and construction in their city development decision-making foundation, and has certain value in practice.