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Logarithmic Entropy Measures for Fuzzy Rough Set and their Application in Decision Making Problem

Logarithmic Entropy Measures for Fuzzy Rough Set and their Application in Decision Making Problem

Omdutt Sharma, Priti Gupta
Copyright: © 2020 |Volume: 9 |Issue: 2 |Pages: 18
ISSN: 2156-177X|EISSN: 2156-1761|EISBN13: 9781522598428|DOI: 10.4018/IJFSA.2020040104
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MLA

Sharma, Omdutt, and Priti Gupta. "Logarithmic Entropy Measures for Fuzzy Rough Set and their Application in Decision Making Problem." IJFSA vol.9, no.2 2020: pp.80-97. http://doi.org/10.4018/IJFSA.2020040104

APA

Sharma, O. & Gupta, P. (2020). Logarithmic Entropy Measures for Fuzzy Rough Set and their Application in Decision Making Problem. International Journal of Fuzzy System Applications (IJFSA), 9(2), 80-97. http://doi.org/10.4018/IJFSA.2020040104

Chicago

Sharma, Omdutt, and Priti Gupta. "Logarithmic Entropy Measures for Fuzzy Rough Set and their Application in Decision Making Problem," International Journal of Fuzzy System Applications (IJFSA) 9, no.2: 80-97. http://doi.org/10.4018/IJFSA.2020040104

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Abstract

Decision-making is a critical problem in various circumstances where some vagueness and ambiguity is found in information. To handle these types of problems, entropy is an important measure of information theory which is exploited to evaluate the uncertain degree of any data. There are two methodologies to determine the entropy, one is probabilistic in nature and other is non-probabilistic. It is shown that for every probabilistic measure there is a corresponding non-probabilistic measure. In this article, some logarithmic non-probabilistic entropy measures have been proposed for the fuzzy rough set corresponding to existing probabilistic entropy measures. The proposed measures are employed in a decision-making problem, which is related to the agriculture. Finally, these proposed measures are compared with the existing trigonometric entropy measures for fuzzy rough sets.

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