The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

Segmentation has several strategic and tactical implications in marketing products and services. Despite hard clustering methods having several weaknesses, they remain widely applied in marketing studies. Alternative segmentation methods such as fuzzy methods are rarely used to understand consumer behaviour. In this study, we propose a strategy of analysis, by combining the Bagged Clustering (B...

in this paper, by introducing two virtual decision-making units (dmus) called ideal dmu (idmu) and anti-ideal dmu (admu) with fuzzy inputs-outputs, the efficiency evaluation of dmus are done by fuzzy data envelopment analysis (fdea). therefore, we evaluate dmus from the perspective of the best and worst possible relative efficiency. for each dmu two efficiencies are calculated while inputs and ...

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...

The present paper deals with formal concept analysis of data with fuzzy attributes. We clarify several points of a new approach of [S.Q. Fan, W.X. Zhang, Variable threshold concept lattice, Inf. Sci., accepted for publication] which is based on using thresholds in concept-forming operators. We show that the extentand intent-forming operators from [S.Q. Fan, W.X. Zhang, Inf. Sci., accepted for p...

In fuzzy control, there is a large amount of parameters involved in the system design. Due to their interdependency, these parameters are sometimes conflicting causing an unavoidable trade-off among performance indices. It is difficult to discern the best combination of fuzzy parameters with respect to a given range of some performance indices. In this case, a clustering technique represents a ...

using greedy clustering method to solve capacitated location-routing problem with fuzzy demands abstract in this paper, the capacitated location routing problem with fuzzy demands (clrp_fd) is considered. in clrp_fd, facility location problem (flp) and vehicle routing problem (vrp) are observed simultaneously. indeed the vehicles and the depots have a predefined capacity to serve the customerst...

Fuzzy control can be interpreted as an approximation technique for a control function based on typical, imprecisely speciied input{output tuples that are represented by fuzzy sets. The imprecision is characterized by similarity relations that are induced by transformations of the canonical distance function between real numbers. Taking this interpretation of fuzzy controllers into account, in o...

The goal of this paper is to show how the concept of fuzzy logic can be used to establish a degree to which an investment project belongs to a class of risk. Also, the probability of the fuzzy event is presented and is ap-plied to calculate the probability of the fuzzy event “the project X is a good investment”. This process has to enable the decision maker to compare several alternative invest...