Research On Knowledge Discovery For The State Of Traffic Flow Based On Rough Set Theory

Recognizing and diagnosing the state of traffic flow is an important research area,which is the basis of improving the level of traffic management and the quality of traffic information services.At present,due to the detection data of traffic flow have some quality problems such as omissions,errors,and redundancy,which will make the recognition result for traffic flow's state become incomplete and inaccurate.Aiming at this problem,scholars put forward many solutions,including attempts to adopt the method of knowledge discovery.Using the method of knowledge discovery can reveal some hidden,unknown and valuable information from the huge amount of traffic flow information,so as to provide rules and decision-making basis for traffic management department.This article focuses on the knowledge discovery for the traffic flow's state based on rough set theory and taking the specific road section of Beijing as an example.Specific research contents are as below:1.Data preprocessing research for the knowledge discovery of traffic flow's state.This chapter mainly analyzed two topics.The first is the characteristics of the detector data,including abnorMal data,error determination standard and abnormal data to fill.The second is designed a data preprocessing algorithm based on filter for traffic flow data.2.Studying the attributes reduction algorithm based on rough set theory in order to apply it in the decision table of traffic flow' state.Taking the attribute reduction algorithm based on discernible matrix as the basis,then introducing the difference function and revising it to make it can be applied into the incompatible decision table.3.Case analysis by using the revised discernible matrix algorithm.Using the actual data collected by sensors from road to study the knowledge discovery process of the traffic flow's state.After finishing several process,including data preprocessing,attribute reduction and rule acquisition,finally obtained the knowledge rules of the traffic flow's state.This paper studies the knowledge discovery method for the traffic flow's state based on rough set theory.This method can extract valuable knowledge and rules by deleting the redundant attributes,which can be used in the research of reccognizing the traffic flow's state.The research result of this paper not only can provide decision-making basis for traffic administrative department,but also can propose new ideas for the study focusing on recognition and diagnosis the state of traffic flow.