Reduction And Model Parameters Soft Rough Sets And Dissemination Of Research

The rough set theory, proposed by Pawlak in the early eighties of the last century, is used to deal with uncertain problems. The knowledge represented by indiscernibility relationship and obtained in the people’s production and life, is used to approximate the description of all given subsets of objects on the universe. Molodtsov proposed soft set theory to solve this kind of problems in the late nineties. The soft set is a subset family about parameters, it just gives an approximate description about every object, and the choice of parameters has not the limiting factors, thus the theory has a greater advantage in the decision-making process.Then some scholars combined the two theory to study. On this basis,we dicuss the parameters reduction of soft rough set, and promote the research on existing model in general binary relation on the universe determined by the soft set in this paper as follows:(1) Based on the soft upper and lower approximations of soft set on Pawlak approximation space by Ma Zhenming,we define the decision-making value of the object, binding the importance of parameters,and obtain the corresponding equivalence relation. Then, binding the existing equivalence relation,we format the equivalence relations family and construct a soft rough divide on the universe.At the same time,we give this parameter reduction ideas and algorithms based on the divide. Because this soft rough divide combines the decision-making ability of the soft set and the classification ability of the original equivalence relation on the universe, through a soft rough set instance about its application to the smart phone to buy, we can get a reasonable result.(2) The soft rough set model proposed by Feng is given on the basis of the division of the universe based on soft set. Giving a general soft set of the universe,we can promote the model. First, unlike the binary relation on previously defined in the same universe, we define the two kinds of soft fuzzy approximation operators on generalized soft approximation space, given by the general binary relation between the parameters and the subsets of the universe on the basis of the soft set mapping. Next, we discuss the nature of these operators and focus on proving the conditions satisfying the duality. And then we give the algorithm of the upper and lower approximation sets by the latter definition. Finally, it is applied in the actual medical diagnosis and treatment system, we get the upper and lower approximate sets, positive and negative domains, as well as the domain of the boundary,based on the set of the patient’s presenting symptoms,. From it,we discuss the similarities and differences of the two approximation operators. the types of the definitions of the former operator and conventional operator are the same, so it is easy to understand, but can not reasonably explain the actual meaning of the approximate set. The latter defined type is rather special, but it is actually natural promotion of the former, can make up for the deficiencies of the former, and the results of the rough approximation are quite ideal. The model has some practical value.