In this paper, rstly we have introduced to entropy of sequences of fuzzy sets and given sometheorems about it. Secondly, the waves P and T which appears in electrocardiograms weretransferred to fuzzy sets, by using denition of entropy for sequences of fuzzy sets, and somenumerical values were obtained for sequences of waves P and T. Thus any person can makea medical predictions for some cardiac...

Combined with weight of samples and kernel function, fuzzy clustering method with generalized entropy is studied. Objective function for fuzzy clustering with generalized entropy based on sample weighting is obtained. Following that, fuzzy clustering algorithm with generalized entropy based on sample weighting is presented. In addition, by introducing kernel into the presented objective functio...

Kernel methods and rough sets are two general pursuits in the domain of machine learning and intelligent systems. Kernel methods map data into a higher dimensional feature space, where the resulting structure of the classification task is linearly separable; while rough sets granulate the universe with the use of relations and employ the induced knowledge granules to approximate arbitrary conce...

Interval-valued intuitionistic fuzzy set (IVIFS) has developed to cope with the uncertainty of imprecise human thinking. In the present communication, new entropy and similarity measures for IVIFSs based on exponential function are presented and compared with the existing measures. Numerical results reveal that the proposed information measures attain the higher association with the existing me...

Fuzzy clustering based on generalized entropy is studied. By introducing the generalized entropy into objective function of fuzzy clustering, a unified model is given for fuzzy clustering in this paper. Then fuzzy clustering algorithm based on the generalized entropy is presented. At the same time, by introducing the spatial information of image into the generalized entropy fuzzy clustering alg...

This article presents a new similarity measure for LR-type fuzzy numbers. The proposed similarity measure is based on a defined metric between LR-type fuzzy numbers. It is known that an exponential operation is highly useful in dealing with the classical Shannon entropy and cluster analysis. We adopted, therefore, the exponential operation on this metric. Furthermore, we analyze its properties ...

In this study we propose a measure of the entropy norm (R, S) for q-row orthopair fuzzy sets (qROFS). The proposed is validated both theoretically and practically to ensure validity. We also simple methodology purpose solving multi-criteria decision-analysis problems using introduced measure. This method takes into account different circumstances criteria weights, such as unknown well other cas...

Fuzzy measures can flexibly describe the relative importance of decision criterion as well as their interactions in multicriteria decision making. Based on the diamond pairwise comparison, a new identification method of 2-order additive fuzzy measure is proposed. The relative weight and the interaction degree can be obtained simultaneously for every pair of criteria in the diamond pairwise comp...

In this paper, we propose new methods to represent interdependence among alternative attributes and experts’ opinions by constructing Choquet integral using interval-valued intuitionistic fuzzy numbers. In the sequel, we apply these methods to solve the multiple attribute group decision-making (MAGDM) problems under interval-valued intuitionistic fuzzy environment. First, the concept of interva...