Based On Rough Set Of Urban Areas When Traffic Green Control System Research

The Urban road traffic congestion and jam has become the world's large and medium cities common phenomenon, traffic intelligent control is to settle this problem with one of the most effective way. Implement intelligent traffic control not only to improve the safety of the traffic, production efficiency and effectiveness, and land resources and related to the rational utilization of energy, environment pollution and noise improved, and the continuous development of the national economy and improve the economic benefits of the society. The urban traffic management the problem to be solved is how to deal with the city modernization brought about by the problem of traffic congestion. But a city traffic often reflected in the regional transportation problem, so the focus of this article is the use of rough sets theory method to analyze the regional transportation, and to set up the whole city green traffic control when the decision support system. Rough set theory is a kind of deal with imprecise, uncertainty and incomplete information of new mathematical tool, it is also the most challenging one of the research and application of field. Rough set theory is the basic idea of uncertain, not accurate knowledge base of knowledge to approximate characterizations.This area traffic control when the way is through green rough set theory decision table reduction algorithm is used for traffic flow reduction in the feasibility study, based on the discernibility matrix attribute of the frequency of attribute reduction algorithm is presented, and the complex traffic flow reduction for simple key crossroads phase, in order to solve the plan selection of control method to realize real-time area traffic control faced by the\" dimension disaste\" problem. Specific it is rough set theory based on the data mining method, with the corner detection data as the research object, by record data form the original decision table, after the adoption of a continuous attributes discretization method directly with supervisory and Semi Naive Scaler algorithm for the improvement of the original decision table data pretreatment, finally to data pretreatment of decision table after based on the discernibility matrix attribute frequency of heuristic reduction algorithm for attribute reduction, that the reduction of the result for the key attributes that key phase, according to procedures for road achieving results provide a basis for the decision-making departments.On regional transportation when green control method based on the research of science of city traffic set up green control when the decision support system of evaluation indexes, and summarizes the research scientific index evaluation method to establish evaluation model, the purpose of which is to effectively study of urban area traffic control when the green to the urban traffic control when the green impact decision-making, can prompt the congestion and key reasons for area, in order to guarantee the sustainable urban traffic flow smoothly.