نتایج جستجو برای: fuzzy entropy

تعداد نتایج: 153390  

Journal: :Entropy 2017
Liwei Zhan Chengwei Li

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...

X. Y. Bai Y. L. Yang

Due to the complexities of objects and the vagueness of the human mind, it has attracted considerable attention from researchers studying fuzzy classification algorithms. In this paper, we propose a concept of fuzzy relative entropy to measure the divergence between two fuzzy sets. Applying fuzzy relative entropy, we prove the conclusion that patterns with high fuzziness are close to the classi...

Journal: :JCP 2010
Xilong Qu Zhongxiao Hao

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...

Journal: :Journal of Mathematical Analysis and Applications 1979

2004
Hongwei Zhu Otman Basir

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...

2004
Qinghua Hu Daren Yu

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...

Journal: :Pattern Recognition Letters 2003
Wenbing Tao Jin-Wen Tian Jian Liu

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, ...

2012
Kai LI Peng LI

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...

2012
Ahmad Jafarnejad Chaghooshi Mohammad Reza Fathi Mojtaba Kashef

Purpose: The aim of this study is applying a new method for Industrial robotic system selection. Design/methodology/approach: In this paper, the weights of each criterion are calculated using fuzzy Shannon’s Entropy. After that, fuzzy TOPSIS is utilized to rank the alternatives. After that we compare the result of Fuzzy TOPSIS with Fuzzy VIKOR method. Then we select the best Industrial Robotic ...

2013
Fangyan Nie Jianqi Li Qiusheng Rong Meisen Pan Fen Zhang

Human object extraction from infrared image has broad applications, and has become an active research area in image processing community. Combined with chaos differential evolution (CDE) algorithm and morphological operators, a novel infrared human target extraction method is proposed based on nonextensive fuzzy entropy. Firstly, the image was transformed into a fuzzy domain by fuzzy membership...

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