Shannon entropy was defined for probability distributions and then its using was expanded to measure the uncertainty of knowledge for systems with complete information. In this article, it is proposed to extend the using of Shannon entropy to under-defined or over-defined information systems. To be able to use Shannon entropy, the information is normalized by an affine transformation. The const...

In the image acquisition or transmission, the image may be damaged and distorted due to various reasons; therefore, in order to satisfy people’s visual effects, these images with degrading quality must be processed to meet practical needs. Integrating artificial bee colony algorithm and fuzzy set, this paper introduces fuzzy entropy into the self-adaptive fuzzy enhancement of image so as to rea...

Fuzzy clustering is capable of finding vague boundaries that crisp clustering fails to obtain. But time complexity of fuzzy clustering is usually high, and the need to specify complicated parameters hinders its use. In this paper, an entropy-based fuzzy clustering method is proposed. It automatically identifies the number and initial locations of cluster centers. It calculates the entropy at ea...

This paper proposes to use a fuzzy entropy based feature selection approach to reduce the dimensionality of DAIS hyperspectral data. To compare its performance, three other filter based feature selection approaches were used. A support vector machine was used as a classification algorithm. In order to compare various feature selection approaches with full dataset, McNemar’s test based test for ...

The present study aimed at ranking and selecting the superior geothermal project for hydrogen production in 14 provinces of Iran using a multi-objective optimization fuzzy hybrid approach through analyzing the ratio (fuzzy Moora) and expanded entropy weighting method. In this research, the extended entropy weighing method and the Fuzzy-Moora approach were utilized to weigh the criteria and proj...

This paper gives an overview on recent development in fuzzy information measures. After some preliminaries, we summarize briefly some fuzzy entropy measures and their generalizations. The generalizations reviewed are useful for further development in fuzzy information measures.

In this paper we consider the maximum entropy principle with imprecise side-conditions, where the imprecise side-conditions are modeled as fuzzy sets. Our solution produces fuzzy discrete probability distributions and fuzzy probability density functions.