Study Of Coving Rough Set

Today, we are in the tide of information revoluation. The tide of informationization has guided traffic information engineering into intelligent traffic era. The desired information constructing of intelligent transport systems have some typical characteristics, such as multi-source and heterogeneous. Analysis and treatment for the traffic information which has complexity, fuzziness and uncertainty, plays a key role in the development and application of intelligent transport systems. Rough set theory is a mathematical tool of dealing with uncertainties. The theory has applied for the reason analysis, warning of traffic congestion and traffic accident, and obtains many research achievements. Cover ing rough set model is an important form of generalization for Pawlak rough set model. This paper mainly researches the covering rough set model, including the theory of covering rough set and the approaches of decision table reduction that bases on covering rough set theory.In the aspects of covering rough set theory, this study mainly researches the covering rough set models based on general covering and neighborhood system which is generated from covering, and discusses complete completely distributive lattices (referred to as the CD lattice) based covering rough sets.(1) For the rough set model based on general covering, this paper first reviews the related work of Bonkowski about covering rough sets and proposes the covering rough set model based on the single coverage and studies the relevant basic properties of the approximation operators; and this paper gives characteristics of the upper and lower approximation operators in the sense of expansion equal, and gives a number of necessary conditions on which the covering is the single covering and the judging theorem of single covering in approximate space based on improved approximate operators.(2) For the rough set model based on the neighborhood system, this paper focuses on the research of the rough set models based on smallest neighborhood and the one based on minimal description. As the common forms of these two rough approximation operators, we define five kinds of upper and lower approximation operators (I)-(V), and discuss their properties and their relationship, and construct the topological spaces based on these approximation operators. The paper also researches the relationship among the approximate operators and the inner operator, closure operator in the topological spaces.(3) The approximation spaces and approximation operators based on the CD lattice are important models for the generalizations of the rough set model. Under the framework of CD lattice, it aims to provide a unified description method for a variety of approximation operators. Based on the existing researches, this work gives some properties of approximation operators rooting in the CD-based grid. It also shows improved upper and lower approximation operators that have the properties that the lower approximation operator is closed under intersection and the upper approximation operator is closed under union. Based on the topological molecular lattice theory, it also discusses the topological properties of the approximate operators in the CD-based grid. And it also constructs the topological space of the relevant approximate sets, and discusses the reduction problem of covering and its affection for approximate operators.In the aspect of the covering rough set applications, this paper discusses the reduction theory and method of covering information systems based on the covering rough set model. This paper proposes the concepts of covering reduction and d-covering reduction of covering information system and consistent covering decision table respectively, and also presents the reduction method with the assistance of discernibility matrix and discernibility function. This paper also provides the concepts of positive domain reduction and distribution reduction for the inconsistent covering decision tables, and their judging theorems and the reduction methods with the help of discernibility matrix and discernibility function. The work design reduction algorithm for all the reduction methods above, and also shows the feasibility of the covering rough set model based reduction theory.At last, it’s the conclusion and expectation.