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Urban traffic environment system refers to the city for traffic in all aspects of technology , management strategies , rules and regulations , and urban transportation habits, and some of the major cities in the traffic pollution and traffic congestion problems are all in varying degrees, affect people's everyday life . Urban traffic environment is extremely complex, and a city's transport network environment is quite huge , so the entire city traffic environment for unified intelligent control and optimization is not realistic, it makes a traffic environment partitioning theory , some scholars envisaged entire traffic environment into different small areas , these different small areas have the same properties , and then through the traffic sub- area intelligent optimization reach the entire traffic environment governance and optimization. Based on the inspection and abroad TAZ related papers, results of previous studies , drawing on the experiences of others , based on the clustering method and through in-depth analysis of urban traffic environment , the clustering method is applied to urban traffic environment partitions to go, try according to the similarity evaluation index data for a given traffic maps for traffic partition , the specific contents are as follows : First, the current problems of urban traffic environment to explain the necessity of partitioning the traffic environment ; Second , determine the evaluation index selection . In considering the state of the environment in urban traffic spatial distribution and differences in data sources , operability, and other factors , based on the selection can fully reflect the nature of the transport sub-region corresponding evaluation . First, the entire city traffic environment Alexandra gridded network , each cell has a representative of transport properties of n characteristic index , corresponding to each of the grid can be seen as a pixel , constituted by an n-dimensional vector . Since the non- attainment of the city after the grid transport network can be seen as an image, you can consider using clustering method for urban traffic environment partitions ; third , environmental data for the characteristics of urban traffic analysis ISODATA algorithm and gray poly class methods and practical features and make improvements , then these two methods used to partition the traffic environment ; fourth , with the DS evidence reasoning theory to the classification of uncertainty generated during sample processing ; fifth on this article the content of the study were studied and discussed.
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