Study On Fuzzy ββ-covering Rough Set Models And Application

In the era of big data,the uncertainty of data and information acquired by people in various fields generally increases,and all kinds of things tend to be diversified and fuzzy.Faced with massive and complex information,many mathematical concepts for judgment and decision have emerged.At present,fuzzy decision is more and more common in daily production and life.Information system is one of the important means to deal with fuzzy decision.When it comes to making decisions,some people are more cautious in making decisions,often consider the worst case and always hold a negative attitude;On the other hand,some people are very optimistic when making decisions and always hold a positive psychology.If only unilateral factors are considered,it will often lead to one-sided and limited judgment.In order to be more consistent with people’s psychology,considering the difference of people with different personalities in decision-making,this paper proposes a new model for decision-making.The main content of this paper is as follows:(1)In order to integrate multi-level fuzzy information better,a new fuzzy β-covering rough set model based on information system is defined by using fuzzy β-co-neighborhood for the first time.At the same time,the concept of couple approximate operators defined by L.W.Ma is extended to information system,and propose a new model—dyad fuzzy β-covering rough set models,which is a combination of covering rough set theory,fuzzy rough set theory and fuzzy information system.This model can analyze and solve practical problems from both positive and negative aspects,so as to make more accurate decisions.This paper takes medicine as an example to illustrate its application value.At the same time,we extend the above model to fuzzy lattice,and construct the L-dyad fuzzy β-covering rough set models.(2)In the actual situation,the amount of data is usually very large.In order to make the model more convenient to deal with large and complex data,this paper uses matrix to represent the model,and realizes the machine-realization of the model,which is realized by computer programming.Finally,this paper uses Matlab to solve a practical problem to illustrate the value of the model.In addition to adapting to the needs of knowledge innovation,scientific and technological progress and discipline development,colleges and universities also need to comprehensively consider the professional needs of various disciplines and students’acceptance of the courses offered by the major,so as to better meet the needs of students to receive high-quality higher education and optimize the discipline structure.In this paper,50 majors in the database are selected to meet the professional needs of nine disciplines in high school,and the final exam scores of students in a senior high school are collected,from which 500 samples are randomly selected.For a major in a university,the dyad fuzzy β-covering rough set models constructed in this paper is used to evaluate the degree of matching between the major and students.The validity and superiority of the model are verified by data analysis and comparative study.