Fuzzy set-based methods contribute to the formalization of different types of approximate reasoning, mainly in two ways. First, when modeling classes and properties, fuzzy sets naturally encode gradual properties, such as, e.g., 'large', whose satisfaction is a matter of degree and may be only partial for particular instances. Due to this ability, fuzzy sets are naturally entitled to capture in...

Engine fault has a high rate in the car. Considering about the distinguishing feature of the engine, Engine Diagnosis Expert System was investigated based on Diagnosis Tree module, Fuzzy Neural Network module, and commix reasoning module. It was researched including Knowledge base and Reasoning machine, and so on. In Diagnosis Tree module, the origin problem was searched in right method. In whi...

in this article the methodology proposed by li and wang for mixed qualitative and quantitative modeling and simulation of temporal behavior of processing unit is reexamined and extended to more complex case. the main issue of their approach considers the multivariate statistics of principal component analysis (pca), along with clustered fuzzy digraphs and reasoning. the pca and fuzzy clustering...

Human reasoning is characterized by a degree of fuzziness and uncertainty. In the present paper we develop a fuzzy model for a better description of the reasoning process and we use the fuzzy systems’ total possibilistic uncertainty as well as the classical Shannon’s entropy (properly modified for use in fuzzy environments) in measuring the individuals’ reasoning skills. Classroom experiments a...

Ontologies have been successfully employed in applications that require semantic information processing. However, traditional ontologies are not able to express fuzzy or vague information, which often occurs in human vocabulary as well as in several application domains. In order to deal with such restriction, concepts of fuzzy set theory should be incorporated into ontologies so that it is poss...

Edge detection is an indispensable part of image processing. In this paper, a novel edge detection method based on multiple features and fuzzy reasoning is proposed, in which the limitations of gradient-based edge detection methods and present fuzzy edge detection algorithms can be overcome. The new method selects trapezoid fuzzy membership functions, defines multiple features for each pixel fr...