On Some Properties of Entropy of Fuzzy Numbers

Dhar, Mamoni

doi:10.5815/ijisa.2013.03.07

Cited by 7 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Entropy weight is a parameter that describes how much diverse alternatives approach one another with respect to a certain criteria [ 3 , 28 ]. This concept is also, relatively known in the measurement of fuzziness [ 38 ]. Hence this method is suitable to be applied in our approach as we will deal with fuzzy data.…”

Section: Hamming Distance Methods and Subjective And Objective Weigmentioning

confidence: 99%

Hamming Distance Method with Subjective and Objective Weights for Personnel Selection

Saad

Ahmad

Abu

et al. 2014

The Scientific World Journal

View full text Add to dashboard Cite

Multicriteria decision making (MCDM) is one of the methods that popularly has been used in solving personnel selection problem. Alternatives, criteria, and weights are some of the fundamental aspects in MCDM that need to be defined clearly in order to achieve a good result. Apart from these aspects, fuzzy data has to take into consideration that it may arise from unobtainable and incomplete information. In this paper, we propose a new approach for personnel selection problem. The proposed approach is based on Hamming distance method with subjective and objective weights (HDMSOW's). In case of vagueness situation, fuzzy set theory is then incorporated onto the HDMSOW's. To determine the objective weight for each attribute, the fuzzy Shannon's entropy is considered. While for the subjective weight, it is aggregated into a comparable scale. A numerical example is presented to illustrate the HDMSOW's.

show abstract

Section: Hamming Distance Methods and Subjective And Objective Weigmentioning

confidence: 99%

Hamming Distance Method with Subjective and Objective Weights for Personnel Selection

Saad

Ahmad

Abu

et al. 2014

The Scientific World Journal

View full text Add to dashboard Cite

show abstract

“…In this case, by analogy with the entropy (Dhar 2013) (which takes into account both the support and the membership), the uncertainty degree of the discretized NFS is calculated as follows:…”

Section: Proposed Algorithmmentioning

confidence: 99%

Computational Algorithm and Tools of Fuzzy Arithmetic Based on the Principle of Maximum Entropy

Sveshnikov¹,

Bocharnikov²

2022

Preprint

View full text Add to dashboard Cite

The standard fuzzy arithmetic introduced by Zadeh is not always suitable for solving applied problems in various fields of science, technology and business. Even in the case of a small sequence of arithmetic operations (for example, when calculating forecast estimates of business profits), the support of the resulting fuzzy number becomes very large. It is difficult to make a decision about investing if the maximum and minimum of the expected profit differ several times. Therefore, the authors developed an algorithm which forms the result of an arithmetic operation as a subset of a fuzzy binary relation and which implements the principle of maximum entropy. This algorithm allows performing arithmetic operations on fuzzy numerical sets with an arbitrary form of the membership function. Compared to standard fuzzy arithmetic, the proposed algorithm provides a much smaller increase in the support of the resulting fuzzy number. We implemented the algorithm in an add-in for Microsoft Excel, which readers can download and use for applied calculations for free.

show abstract

“…This was discussed in more details in Dhar [20]. So me properties of fuzzy entropy are observed which are the results of the new definition of entropy of fuzzy sets, Dhar [22] and these properties are listed below:…”

Section: New Definition Of Entropy Of Fuzzy Numbersmentioning

confidence: 99%

The Complement of Normal Fuzzy Numbers: An Exposition

Dhar¹,

Baruah²

2013

IJISA

Self Cite

View full text Add to dashboard Cite

Abstract-In this article, our main intention is to revisit the existing definit ion of co mplementation of fu zzy sets and thereafter various theories associated with it a re also commented on. The main contribution of this paper is to suggest a new definit ion of complementation of fuzzy sets on the basis of reference function. So me other results have also been introduced whenever possible by using this new definit ion of complementation.

show abstract

On Some Properties of Entropy of Fuzzy Numbers

Cited by 7 publications

References 9 publications

Hamming Distance Method with Subjective and Objective Weights for Personnel Selection

Hamming Distance Method with Subjective and Objective Weights for Personnel Selection

Computational Algorithm and Tools of Fuzzy Arithmetic Based on the Principle of Maximum Entropy

The Complement of Normal Fuzzy Numbers: An Exposition

Contact Info

Product

Resources

About