Multi attribute decision making methods are considered as one of the most useful methods for solving ranking problems. In some decision making problems, while the alternatives for corresponding criteria are compared in a pairwise comparison manner, if the criteria are inherently fuzzy, debates will arise in ranking alternatives due to the closeness of the values of the criteria. In this researc...

Beginning with triangular fuzzy inputs representing fuzzy ratio judgments, we experiment with two procedures to obtain fuzzy relative priorities in the Analytic Hierarchy Process. We extend the simple geometric mean and simple normalized column sum methods with fuzzy arithmetic. When the pairwise comparisons are fully consistent the methods produce identical results, but they diverge in the pre...

Machines are one of the most important production elements used by companies in phase. Sudden deterioration machinery creates a process that can lead to halt and therefore delay orders. For this reason, enterprises decide replace their old machines with newer technological machines. This replacement decision is not easy as it includes many criteria there alternative on market. From point view, ...

different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (ffls) i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. to the best of our knowledge, there is no method in the literature for finding the non-negative solution of a ffls without any restriction on the coefficient matrix. in this paper a new computational method is ...

Fuzzy methods in remote sensing have received growing interest for their particular value in situations where the geographical phenomena are inherently fuzzy. A fuzzy approach is investigated for the classi® cation of sub-urban land cover from remote sensing imagery and the evaluation of classi® cation accuracy. Under the fuzzy strategy, fuzziness, intrinsic to both remotely sensed data and gro...

Interval-valued data can find their practical applications in such situations as recording monthlyinterval temperatures at meteorological stations, daily interval stock prices, etc. The primary objectiveof the presented paper is to compare three different methods of fuzzy clustering for interval-valuedsymbolic data, i.e.: fuzzy c-means clustering, adaptive fuzzy c-means clustering a...

This paper presents a fuzzy perceptron as a generic model of multilayer fuzzy neural networks, or neural fuzzy systems, respectively. This model is suggested to ease the comparision of diierent neuro{fuzzy approaches that are known from the literature. A fuzzy perceptron is not a fuzziication of a common neural network architecture, and it is not our intention to enhance neural learning algorit...