Vague Set Theory And It's Application Of Fuzzy Madm

Vague sets theory is a new theory to deal with ambiguous information vague. The most basic features of Fuzzy sets theory is: Each object has a distinct partof the degree F. Affiliation function μ_F(X)assigned to each function attached to a figure between 0 and 1 as its affiliation degree. However we must notice that the figure what Affiliation function μ_F(X) assigned to is just amono-value ,which includes evidence supporting x∈X , but also the evidence objecting to x∈Z.In order to solve the shortage of fuzzy set theory, Gau and Buehrer put forward vague set theory. With the further research and development of AI, vague set being as an important soft calculating method becomes more and more useful.At first I introduce the background and developing situations and prospects, then introduce systemically the basic theory and calculation of vague set, thirdly I put forward a kind of distance measure between the vague set. Finally I present a new vague multi-property decision method which apply TOPSIS method based on using vague set. At the beginning I structure the positive and negative ideal answer by marking function, then define a weighted distance measure between vague answers, draw a conclusion :a approximate degree of each program by calculating the distance between the program and ideal answer. At last I sort the program set by approximate degree and sort out the best program. Emulational calculations show this method effective and practical.