A functional defined on the class of generalized characteristic functions (fuzzy sets), called "entropy", is introduced using no probabilistic concepts in order to obtain a global measure of the indefiniteness connected with the situations described by fuzzy sets. This "entropy" may be regarded as a measure of a quantity of information which is not necessarily related to random experiments. Som...

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1. Introduction Cellular Automata have generated much interest [1,2,3] because of their diverse behavior and usefulness as a discrete model for many processes. Wolfram's 1984 paper on universality and complexity in cellular automata [3,4] described four classes of behavior for automata: class 1 for homogeneous stable behavior, class 2 for simple periodic patterns, class 3 for chaotic aperiodic ...

There exist some several method offer similar functions and current technologies are poor to discriminate the important weights of attributes of enterprise resource planning system, due to the complexity of metrics and involvement of consumer’s vague perception. Entropy method is used to determine the weight of evaluation indexes and establish multi-level fuzzy synthetic evaluation model. Its a...

We discuss the use of the fuzzy measure for representing information about uncertain variables. We describe the relationship between the fuzzy measure and the Dempster-Shafer belief structure. A method for generating the fuzzy measures associated with a D-S belief structure is described. We discuss the use of the Shapley index as a means for providing an entropy for fuzzy measures. We introduce...

A fuzzy aspect is introduced into L systems and some of its properties are investigated. The relationship between fuzzy L languages and the fuzzy languages generated by fuzzy grammar defined by Lee and Zadeh is elucidated. The concept of fuzzy entropy of a string is proposed as a measure of fuzziness of the latter. Some relationship between fuzzy L systems and the ordinary L systems is discussed.

In this paper incomplete quantitative data has been dealt by using the concept of fuzzy entropy. Fuzzy entropy has been used to extrapolate the data pertaining to the compressor current. Certain attributes related to the compressor current have been considered. Test data of compressor current used in this knowledge discovery algorithm knows the entire attribute clearly. The developed algorithm ...

Uncertainty is inherent in spatial data and spatio-temporal phenomena. Spatial data uncertainty generally refers to error, inexactness, fuzziness and ambiguity. The goals of research on spatial data uncertainty are to investigate how uncertainties arise, or are created and propagated in the spatial data process. Based on information theory, considering the characteristics of randomicity of posi...

This paper presents two variants of pentavalued representation for neutrosophic entropy. The first is an extension of Kaufman's formula and the second is an extension of Kosko's formula. Based on the primary three-valued information represented by the degree of truth, degree of falsity and degree of neutrality there are built some penta-valued representations that better highlights some specifi...

In this paper, we propose a novel approach for image segmentation via fuzzification of Rènyi Entropy of Generalized Distributions (REGD). The fuzzy REGD is used to precisely measure the structural information of image and to locate the optimal threshold desired by segmentation. The proposed approach draws upon the postulation that the optimal threshold concurs with maximum information content o...