In complex network analysis, fuzzy community detection is a challenging task that aims to reveal the network structure by assigning each vertex quantitative membership-degrees to various communities. In this paper, we propose a fuzzy community detection method that iteratively propagates membership-degrees of all vertices. In each iteration, a candidate seed vertex of a potential community is f...

In pattern recognition, feature extraction techniques have been widely employed to reduce the dimensionality of high-dimensional data. In this paper, we propose a novel feature extraction algorithm called membership-degree preserving discriminant analysis (MPDA) based on the fisher criterion and fuzzy set theory for face recognition. In the proposed algorithm, the membership degree of each samp...

Classification is an important topic in data mining research. It is concerned with the prediction of the values of some attribute in a database based on other attributes. To tackle this problem, most of the existing data mining algorithms adopt either a decision tree based approach or an approach that requires users to provide some userspecified thresholds to guide the search for interesting ru...

Can the vague meanings of probability terms such as doubtful, probable, or likely be expressed as membership functions over the [0, 1] probability interval? A function for a given term would assign a membership value of /ero to probabilities not at all in the vague concept represented by the term, a membership value of one to probabilities definitely in the concept, and intermediate membership ...

In this paper, considers the usage of intuitionistic fuzzy numbers in decision making. The values and ambiguities of the membership degree and the non-membership degree for trapezoidal intuitionistic fuzzy number are defined as well as the value-index and ambiguity-index. The proposed ranking method is easily implemented and has a natural interpretation. 2010 AMS Classification: 47S20, 03E72

Let A be any nonrecursive set. For each k 0, we show that there are functions (k + 1)-truth-table reducible to A that are not k-weak-truth-table reducible to A; and we show that there are functions (k + 1)-Turing reducible to A that are not k-Turing reducible to A. Intuitively, this means that k + 1 queries to a nonrecursive oracle are strictly more useful than k queries to the same oracle (for...

In the literature, there are a lot of methods concerning the problem of ordering the interval numbers k , ~ ] , [y,g], ... (', ') or the fuzzy ones A, B , ... (see 4, and for a n overview of methods). All of these methods can be classified a s belonging t o two different approaches. (i) Ordering t h e crisp or the fuzzy intervals using binary order relations: [ c , ~ ] 4 [ y , ~ ] , A 5 B, .......

The following theorems on the structure inside nonrecursive truth-table degrees are established: D egtev's result that the number of bounded truth-table degrees inside a truth-table degree is at least two is improved by showing that this number is innnite. There are even innnite chains and an-tichains of bounded truth-table degrees inside the truth-table degrees which implies an aarmative answe...

We present a new algorithm for computing a SAGBI basis up to an arbitrary degree for a subalgebra generated by a set of homogeneous polynomials. Our idea is based on linear algebra methods which cause a low level of complexity and computational cost. We then use it to solve the membership problem in subalgebras.

Classical automata theory can not deal with uncertainty. To deal with uncertainty in system modeling, fuzzy automata come into the existence. Fuzzy automaton depends on membership value. For finding the membership degree of strings in fuzzy automata, the concept of max – min automaton and min – max automaton can be used. Many researchers have used the concept of max – min automaton for finding ...