An approach based on interval belief degrees and fuzzy evidential reasoning analytical algorithm is developed for multi-criteria decision problems with uncertainties. The criteria weights are represented by interval numbers and criteria values by triangular intuitionistic fuzzy numbers. The proposed approach does not need to utilize the theories such as arithmetic operations for Triangular intu...

This paper presents a new version of fuzzy support vector machine to forecast the nonlinear fuzzy system with multi-dimensional input variables. The input and output variables of the proposed model are describedas triangular fuzzynumbers. Thenby integrating the triangular fuzzy theory andv-support vector regression machine, the triangular fuzzy v-support vector machine (TFv-SVM) is proposed. To...

Pattern classification is one of the most important topics for machine learning research fields. However incomplete data appear frequently in real world problems and also show low learning rate in classification models. There have been many researches for handling such incomplete data, but most of the researches are focusing on training stages. In this paper, we proposed two classification meth...

For multiple attribute group decision-making problems, in which the attribute values are triangular intuitionistic fuzzy numbers and the attribute weight information is the linguistic evaluation, a multiple attribute group decision-making method is proposed. In the method, first, to transform the 2-tuple linguistic attribute weights to the real numbers. Then, to aggregate the experts’ preferenc...

Because of the complexity of limitation and realistic decision of decision knowledge, multiple attribute decision making problems with the attribute value often need to characterize fuzzy number. The triangular fuzzy number to describe this kind of ambiguity is very effective and for the project investment selection problem with triangular fuzzy numbers, this study puts forward a new multiple a...

In crisp production inventory problem, let q, a, b, d, R and r be the quantity produced per cycle, the holding cost, production cost, production quantity per day, the total demand quantity and the demand quantity per day, respectively. We consider three fuzzification methods. Firstly, we fuzzify q, a, b, d, R and r to triangular fuzzy numbers. Secondly, we fuzzify d and r to triangular fuzzy nu...

The aim of this paper is to introduce a new methodology for micro-pattern analysis in digital images. The gray-level pixels’ structure in an image neighborhood describes a spatial specific context. Edge, line, spot, blob, corner or texture can be described by this structure. The gray-level values of the image pixel are interpreted as a fuzzy set, and each pixel gray-level as a fuzzy number. A m...

In many real life problems, the parameters used to characterize the uncertainty or vagueness or impreciseness in information are either triangular or trapezoidal fuzzy numbers. But it is not always possible to restrict the membership function to either triangular or trapezoidal form. In this paper, a new form of non-normal fuzzy number named as Heptagonal fuzzy number is introduced and its arit...

Analytical structure for a fuzzy PID controller is introduced by employing two fuzzy sets for each of the three input variables and four fuzzy sets for the output variable. This structure is derived via left and right trapezoidal membership functions for inputs, trapezoidal membership functions for output, algebraic product triangular norm, bounded sum triangular co-norm, Mamdani minimum infere...

This paper proposes a new method for finding fuzzy weights in the fuzzy analytic hierarchy process (FAHP), which fuzzifies the derived formulation of an eigenvector directly. The presented formulation only needs information about the upper triangular matrix and the assumption about the reciprocal matrix is not necessary. This characteristic makes the FAHP feasible because the property of recipr...