The choice of membership functions plays an essential role in the success of fuzzy systems. This is a complex problem due to the possible lack of knowledge when assigning punctual values as membership degrees. To face this handicap, we propose a methodology called Ignorance functions based Interval-Valued Fuzzy Decision Tree with genetic tuning, IIVFDT for short, which allows to improve the per...

Recently, there is a growing attention by the researchers to solve and interpret the analysis of fully fuzzy linear programming problems in which all of the parameters as well as the decision variables are considered as fuzzy numbers. Under a fully uncertain environment where all of the data are stated as fuzzy, presenting the reasonable range of values for the decision variables may be compara...

Previous papers have described a computational approach to System of Systems (SoS) development using an Agent-Based Model (ABM). This paper describes the Fuzzy Decision Analysis used in the negotiation between the SoS agent and a System agent in the ABM of an Acknowledged SoS development. An Acknowledged SoS has by definition a limited influence on the development of the individual Systems. The...

variables Continuity theorems and chance distribution of random fuzzy Email alerting service here right-hand corner of the article or click Receive free email alerts when new articles cite this article-sign up in the box at the top A random fuzzy variable is a function from a possibility space to the set of random variables. In this paper, some mathematical properties of a random fuzzy variable...

The fuzzy analytic hierarchy process (AHP) is an extension to the classical AHP that enables dealing with the impreciseness and vagueness of judgments. It has been frequently used for handling complex decision making problems that demand a group rather than a single decision maker. Group decision making aggregates the judgments of individuals into a joint decision. Although consensus is the des...

Fuzzy theory provides a rigorous, flexible approach to the problem of defining and computing. Therefore, to facilitate decision-making in geographic information system (GIS), the graph layer indicator and the Takagi Sugeno (TS) fuzzy model have to be integrated. This study explains several versions of the TS fuzzy model based on fuzzy theory and fuzzy operation. An inference model is constructe...

In real decision situations a decision maker (DM) is often confronted with the problem that the information which is necessary for constructing a classical decision model is not available, or the cost for getting this information seems too high. Subsequently, the DM abstains from constructing a decision model; the DM fears that this model is not an authentic image of the real problem. Fuzzy set...

Fuzzy representations of a real-valued random variable have been introduced with the aim of capturing relevant information on the distribution of the variable, through the corresponding fuzzy-valued mean value. In particular, characterizing fuzzy representations of a random variable allow us to capture the whole information on its distribution. One of the implications from this fact is that tes...

  Multiple criteria decision making (MCDM) problem is one of the famous different kinds of decision making problems. In more cases in real situations, determining the exact values for MCDM problems is difficult or impossible. So, the values of alternatives with respect to the criteria or / and the values of criteria weights, are considered as fuzzy values (fuzzy numbers). In such conditions, th...

ranking fuzzy numbers plays a very important role in linguistic decision making and other fuzzy application systems. in spite of many ranking methods, no one can rank fuzzy numbers with human intuition consistently in all cases. shortcoming are found in some of the convenient methods for ranking triangular fuzzy numbers such as the coefficient of variation (cv index), distance between fuzzy set...