TOPSIS is one of the major techniques in dealing with multiple criteria decision making (MCDM) problems, and Belief Structure (BS) model and Fuzzy BS model have been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with Fuzzy BS model is proposed to solve Group Belief MCDM problems. Firstly, the Group Belief MCDM problem is s...

This research aims to determine the maximum or minimum value of a Fuzzy Support Vector Machine (FSVM) Algorithm using optimization function. SVM is considered as an effective method data classification, opposed FSVM, which less on large and complex because its sensitivity outliers noise. One techniques used overcome this inefficiency fuzzy logic with ability select right membership function, si...

in this paper, by using a new approach on distance between two fuzzy numbers, we construct a new ranking system for fuzzy number which is very realistic and also matching our intuition as the crisp ranking system on r.

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the Lagrangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the crossvalidation procedure for selecting the o...

Risk response planning is one of the main phases in the project risk management and has major impacts on the success of a large-scale project. Since projects are unique, and risks are dynamic through the life of the projects, it is necessary to formulate responses of the important risks. The conventional approaches tend to be less effective in dealing with the impreciseness of risk response p...

A reliable and accurate similarity measurement between two software projects has always been a challenge for analogy-based software cost estimation. Since the effort for a new project is retrieved from similar historical projects, it is essentially to use the appropriate similarity measure that finds those close projects which in turn increases the estimation accuracy. In software engineering l...

In this contribution, we first introduce the concept of metrical T-norm-based similarity measure for hesitant fuzzy sets (HFSs) {by using the concept of T-norm-based distance measure}. Then,the relationship of the proposed {metrical T-norm-based} similarity {measures} with the {other kind of information measure, called the metrical T-norm-based} entropy measure {is} discussed. The main feature ...

In this article we propose a new measure of similarity for intuitionistic fuzzy sets. The proposed measure takes into account not only a pure distance between elements but measures the whole missing information which may be necessary to say if the considered elements are more similar or more dissimilar. It is shown that even if a distance between objects is small it can happen that the objects ...