Current Issue : January - March Volume : 2015 Issue Number : 1 Articles : 7 Articles
The aim of this paper is to develop an effective method for solving bimatrix games with payoffs of intuitionistic fuzzy value. Firstly,\nbimatrix game model with intuitionistic fuzzy payoffs (IFPBiG) was put forward. Secondly, two kinds of nonlinear programming\nalgorithms were discussed with theNash equilibrium of IFPBiG. Thirdly,Nash equilibrium of the algorithm was proved by the fixed\npoint theory and the algorithm was simplified by linear programming methods. Finally, an example was solved through Matlab; it\nshowed the validity, applicability, and superiority...
As a hot topic in supply chainmanagement, fuzzy method has been widely used in logistics center location selection to improve the\nreliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative\nfactors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this\npaper proposes amulticriteria decisionmakingmodel based on credibility of decision makers by introducing priority of consistency\nand historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision\nmakers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to\nillustrate howto use themodel.Theresult shows that the fuzzymulticriteria decisionmakingmodel based on credibility mechanism\ncan improve the reliability and suitability of site selection for the logistics center...
This paper proposes a new method for solving fuzzy system of linear equations with crisp coefficients matrix and fuzzy or interval\nright hand side. Some conditions for the existence of a fuzzy or interval solution of ???? Ã?â?? ???? linear system are derived and also a\npractical algorithm is introduced in detail. The method is based on linear programming problem. Finally the applicability of the\nproposed method is illustrated by some numerical examples...
Combining rough sets and fuzzy soft sets,we propose an algorithmto obtain the optimal decision program. In this algorithm, firstly,\naccording to fuzzy soft sets, we build up information systems; secondly, we compute the significance of each parameter according to\nrough set theory; thirdly, combining subjective bias, we give an algorithm to obtain the comprehensive weight of each parameter; at\nlast, we put forward a method to choose the optimal program. Example shows that the optimal algorithm is effective and rational....
Tactile graphics are images that use raised surfaces so that a visually impaired person can feel them. Tactile maps are used by\nblind and partially sighted people when navigating around an environment, and they are also used prior to a visit for orientation\npurposes. Since the ability to read tactile graphics deeply depends on individuals, providing tactile graphics individually is needed.\nThis implies that producing tactile graphics should be as simple as possible. Based on this background, we are developing a system\nfor automating production of tactile maps from hand-drawn figures. In this paper, we first present a pattern recognition method\nfor hand-drawn maps. The usability of our system is then evaluated by comparing it with the two different methods to produce\ntactile graphics....
The optimistic multigranulation T-fuzzy rough set model was established based on multiple granulations under T-fuzzy\napproximation space by Xu et al., 2012. From the reference, a natural idea is to consider pessimistic multigranulation model in\nT-fuzzy approximation space. So, in this paper, the main objective is to make further studies according to Xu et al., 2012. The\noptimistic multigranulation T-fuzzy rough set model is improved deeply by investigating some further properties. And a complete\nmultigranulation T-fuzzy rough set model is constituted by addressing the pessimistic multigranulation T-fuzzy rough set. The\nfull important properties of multigranulation T-fuzzy lower and upper approximation operators are also presented. Moreover,\nrelationships between multigranulation and classical T-fuzzy rough sets have been studied carefully. From the relationships, we\ncan find that the T-fuzzy rough set model is a special instance of the two new types of models. In order to interpret and illustrate\noptimistic and pessimistic multigranulation T-fuzzy rough set models, a case is considered, which is helpful for applying these\ntheories to practical issues....
Lift, leverage, and conviction are three of the best commonly known interest measures for crisp association rules. All of them are\nbased on a comparison of observed support and the support that is expected if the antecedent and consequent part of the rule were\nstochastically independent. The aim of this paper is to provide a correct definition of lift, leverage, and conviction measures for\nfuzzy association rules and to study some of their interesting mathematical properties....
Loading....