Abstract: The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) has been used to propose a new method for filtering time series originating from nonlinear systems. The filtering method is based on fuzzy entropy and a new waveform. A new waveform is defined wherein Intrinsic Mode Functions (IMFs)—which are obtained by CEEMDAN algorithm—are firstly sorted in ascending o...

We introduce an axiomatic approach to entropies and relative that relies only on minimal information-theoretic axioms, namely monotonicity under mixing data-processing as well additivity for product distributions. find these axioms induce sufficient structure establish continuity in the interior of probability simplex meaningful upper lower bounds, e.g., we every entropy satisfying must lie bet...

The entropies of structure, information and the effectiveness entropy between knowledge and organization structure are main entropy sources of supply chain network. Entropy model of fractal supply chain network organization structure is established. Moreover, the basic principle and process of fuzzy AHP are introduced. Fractal knowledge management network outside independently organization stru...

This paper presents an adaptive fuzzy evidential reasoning approach, for segmenting multi-modality MR brain images. A novel fuzzy evidence structure model is proposed under the assumption that each information source provides two types of evidence: probabilistic evidence and fuzzy evidence. A new information measure, called hybrid entropy, is employed for evaluating the overall uncertainty cont...

Rough set theory has attracted much attention in modeling with imprecise and incomplete information. A generalized approximation space, called fuzzy probability approximation space has been proposed by introducing probability into fuzzy approximation space. The novel definition combines three types of uncertainty into a model. Information or knowledge is considered as a partition of the univers...

In this paper, we first use a fuzzy preference relation with a membership function representing preference degree forcomparing two interval-valued fuzzy numbers and then utilize a relative preference relation improved from the fuzzypreference relation to rank a set of interval-valued fuzzy numbers. Since the fuzzy preference relation is a total orderingrelation that satisfies reciprocal and tra...

In the paper, a three-level thresholding method for image segmentation is presented, based on probability partition, fuzzy partition and entropy theory. A new fuzzy entropy has been defined through probability analysis. The image is divided into three parts, namely, dark, gray and white part, whose member functions of the fuzzy region are Z-function and P-function and S-function, respectively, ...

Fuzzy entropy clustering is an improved fuzzy C-means algorithm and is proposed in the past years. In this paper, by introducing the generalized entropy into fuzzy clustering, we obtain the objective function of the generalized entropy, and use neural networks and the augmented Lagrange method to solve the optimization problem with objective function of generalized entropy. Afterwards, we prese...