Based On Cut Set Of Fuzzy Rough Sets And Its Roughness,

Intelligent information proceeding is a very hot point in theory and application of information science.With the participation of human,the uncertainty of data and information system becomes more and more delighted. How to mine the potential and valuable information from a lot of messy and strong-ditracted data has given human the unprecedented challenge in intelligent information process. So it generated a new field of artificial intelligence research-data mining. Although there have been a lot of statistic technology about proceeding data, the advanced intelligent data analasy technology hasn't been matured. So the gap between data information and its understanding becomes more and more large .The rough set theory was put forward by Professor Pawlak ,Poland University of Science and Technology, as a method to study the expression and learning of uncomplete or uncertain knowledge base .It was attached importance by many scholars around the world. It also can be seen a lot of papers about rough set and its application. They come from many fields such as computer, control and decision field, management and financial engineering field, medical engineering field, etc. This can reflect rough set theory has entered many fields as a tool of proceeding data. The aim which rough set theory study is a aim set that is described by a muti-value attribution. For every aim and its attribution,there has a value as its described charter aim, attribution and its described charter are the three basic factors to expression decision problems. This expressing way can also be regarded as a two-demension charter whose line are corresponded with aim and arrows are corresponding with attributions. Every lines includes description character of corresponding information and information about classification of aims. Generally, what we can get of aims can't classify them, which leads to the indicernablity. Rough set theory make use of the upper approximation and lower approximation made from indicernablity to describe it. These approximations are corresponded with the maximum set belonging to the given classification and the minimum set belonging to the given classification respectively.Fuzzy set theory was put forward by Zadeh in 1965,the expert in control of American, as a mathematician tool to proceed inaccurate phenomenon. In classic set theory, one element can be denoted by a character function about whether belongs to a set . If it belongs to A ,then A(x)=l,or A(x)=0. but in fact, the edge of things are not accurate , so we introduced theconcept of membership function to denote the deepness of element x belongs to set A . When we describe the fuzzy concept of approximate space in rough set theory, the fuzzy rough set was generated correspondingly.This paper has a discussion on a kind of fuzzy rough set model based on the cut-set ,(the third chapter),it makes the relation of fuzzy rough set and classic rough set by the cut-set of a fuzzy set. Lastly we give the rough measure of a fuzzy rough set under -cut-set (the forth chapter)...