Research On Reduction Algorithm Of Rough Set And Its Application

Rough set theory is independent of any foregoing information which is excluded of processed data sets, and it is a new effective mathematic tool to deal with the uncertainty, imprecision and incompletion. Since the end of 1980s, rough set has become hotspot gradually in the intellectual information processing field.Knowledge reduction is a kernel problem in the research of rough set theory. The reduction algorithm based on the rough set theory can be used in the areas of knowledge acquisition, machine learning, decision analysis, modeling and so on, and it is related to intelligent control nearly. However, knowledge reduction is dependent on a series of supporting algorithms such as the calculation of attribute significance, finding core, attribute reduction and value reduction. Design and implementation of reduction algorithm is one of important contents of rough set research. The purposes of this paper are researching a simple and effective reduction method and furthermore resolving fuzzy information system problem with rough set method, at the same time, discussing the application of rough set in control.Firstly, it is researched of existing relative reduction algorithms in Decision Information System in this paper. A novel reduction method based on the binary discernibility matrix is presented. In this reduction method, binary discernibility matrix and its operation rules are defined based on rough set, homologous prove of operation rules are given at the same time. In addition, minimal reduction discrimination and calculation method about attribute significance of binary discernibility matrix are redefined. Based on the definitions, finding core algorithm, relative attribute reduction algorithm and value reduction of information decision system are presented based on binary discernibility matrix. The algorithms are programmed by MATLAB. The proposed algorithms of binary discernibility matrix rely mainly on bit operation without complicated logic minimization and set operation. Therefore, compared to traditional reduction model, the advantage of novel method is that, calculation is simplified to some extent and reduction efficiency is improved to a certain extent. Reduction can be get only through binary matrix operation rather than depending on the concrete comment of information decision table. Therefore, the novel method has some generality. This method has been applied in switch circuit integration of digital circuit design and got the logic expression of briefest digital circuit, which can prove the validity of the algorithmSecondly, Rough set theory and fuzzy set theory are compared in this paper. The reduction method based on binary discernibility matrix has been applied in attribute reduction of a fuzzy information system. This algorithm is compared to others and an example is given to illustrate the validity of the algorithm.Finally, reduction algorithm of rough set theory and fuzzy reasoning mechanism are combined to construct a rough fuzzy controller in this paper. Through researching of one-order inverted pendulum it is explained that rough set reduction algorithm is an effective method to get rules; control experience of experts to some object can be objectively expressed through constructing rough fuzzy controller, therefore, it can replace experts to control the objects.