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 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...

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 ...

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...

decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. the resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. the most comprehensible decision trees have been designed for perfect symbolic data. classical crisp decision trees (dt) are widely applied to classification t...

Bankruptcy is one of the most important issues in Financial Management and investment. Numerous studies on Bankruptcy Prediction have been carried out considering Quantitative factors and they applied different techniques on it to predict Bankruptcy, while only fewer studies have proposed and considered Qualitative factors for prediction of Bankruptcy and even then failure of bankruptcy persist...

ISSN: 2186-1390 http://www.ijcvsp.com Abstract In this paper, a fuzzy approach for image segmentation based on Tsallis entropy is introduced. This approach employs fuzzy Tsallis entropy to measure the structural information of image and to locate the optimal threshold desired by segmentation. The proposed method draws upon the postulation that the optimal threshold concurs with maximum informat...