This paper presents a fuzzy set theory based approach to Chinese sentence-level sentiment classification. Compared with traditional topic-based text classification techniques, the fuzzy set theory provides a straightforward way to model the intrinsic fuzziness between sentiment polarity classes. To approach fuzzy sentiment classification, we first propose a fine-to-coarse strategy to estimate s...

The purpose of this article is twofold: first to introduce a multi attribute decision making model for radio frequency identification system consisting of four main criteria and five alternatives, and second to develop and solve the proposed fuzzy TOPSIS problem. Author presented an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ...

In data mining, the conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. Fuzzy clustering methods have the potential to manage such situations efficiently. This paper introduces the limitations of conventional clustering methods through k-means and fuzzy c-means clustering and demonstrates the...

Feature subset selection has become an important challenge in areas of pattern recognition, machine learning and data mining. As different semantics are hidden in numerical and categorical features, there are two strategies for selecting hybrid attributes: discretizing numerical variables or numericalize categorical features. In this paper, we introduce a simple and efficient hybrid attribute r...

Interval-valued fuzzy sets involve more uncertainties than ordinary fuzzy sets and can be used to capture imprecise or uncertain decision information in fields that require multiple-criteria decision analysis (MCDA). This paper takes the simple additive weighting (SAW) method and the technique for order preference by similarity to an ideal solution (TOPSIS) as the main structure to deal with in...

Ranking competing alternatives in terms of their overall performance with respect to some criterions in fuzzy environment is possible by the use of fuzzy TOPSIS methodology using interval-valued fuzzy-sets concepts. This author presents an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for prioritizing alter...

Fuzzy set has been applied in many real applications to handle uncertainty. The aim of the paper is to study the replacement problem with uncertainty. This problem involves capital cost, scrap value or salvage value, maintenance cost or operating cost, and rate of interest having an imprecise value. Here, we assume the imprecise values as positive trapezoidal fuzzy numbers. Moreover, we conside...

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. The main aim of this paper is to propose a new approach for the ranking of generalized fuzzy numbers. The proposed ranking approach is based on distance between positive ideal solution and negative ideal solution. The main...

In this paper we propose a fuzzy goal programming method for obtaining a satisfactory solution to a bi-level multi-objective absolutevalue fractional programming (BLMO-A-FP) problems. In the proposed approach, the membership functions for the defined fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables c...

In this paper we consider a global optimization approach for solving fuzzy fractional posynomial geometric programming problems. The problem of concern involves positive trapezoidal fuzzy numbers in the objective function. For obtaining an optimal solution, Dinkelbach’s algorithm which achieves the optimal solution of the optimization problem by means of solving a sequence of subproblems ...