Divergence measures on hesitant fuzzy sets

Kobza, Vladimír; Janiš, Vladimír; Montes, Susana

doi:10.3233/jifs-161430

Cited by 16 publications

(10 citation statements)

References 18 publications

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“…For example, the idea that scores can be used to perform a regression can easily be exported to models based on hesitant fuzzy sets [11,12,[52][53][54][55] for which scores are already available [56][57][58]. It seems also feasible to export it to other hybrid soft set models (cf., Ali et al [59], Fatimah et al [60], Ma et al [16], Zhan and Zhu [14], and Zhan et al [61]).…”

Section: Discussionmentioning

confidence: 99%

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

2017

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Zadeh's fuzzy set theory for imprecise or vague data has been followed by other successful models, inclusive of Molodtsov's soft set theory and hybrid models like fuzzy soft sets. Their success has been backed up by applications to many branches like engineering, medicine, or finance. In continuation of this effort, the purpose of this paper is to put forward a versatile methodology for the valuation of goods, particularly the assessment of real state properties. In order to reach this target, we develop the concept of (partial) valuation fuzzy soft set and introduce the novel problem of data filling in partial valuation fuzzy soft sets. The use of fuzzy soft sets allows us to quantify the qualitative attributes involved in an assessment context. As a result, we illustrate the effectiveness and validity of our valuation methodology with a real case study that uses data from the Spanish real estate market. The main contribution of this paper is the implementation of a novel methodology, which allows us to assess a large variety of assets where data are heterogeneous. Our technique permits to avoid the appraiser's subjectivity (exhibited by practitioners in housing valuation) and the well-known disadvantages of some alternative methods (such as linear multiple regression).

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Section: Discussionmentioning

confidence: 99%

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

2017

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“…Mishra et al 8 discussed the discrimination measures‐based EDAS model to solve the healthcare waste (HCW) assessment problem. In the recent past, several discrimination measures have been proposed for IFSs, IVIFSs and hesitant fuzzy sets (HFSs), and they have been utilized for different perspectives 31,33–35 . However, very few authors have concentrated on the discrimination measure for PFSs.…”

Section: A Novel Discrimination Measure and Score Function In The Pfss Contextmentioning

confidence: 99%

Pythagorean fuzzy weighted discrimination‐based approximation approach to the assessment of sustainable bioenergy technologies for agricultural residues

et al. 2021

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The inappropriate dumping of agricultural residues (ARs) can result in environmental pollution and the waste of valuable energy resources. The process of converting ARs to energy has been considered an important step for regional energy, agricultural development, and environmental sustainability and recently, many sustainable bioenergy technologies (BETs) have been developed for ARs. Since the assessment of ARs‐to‐energy conversion technologies contains several alternatives concerning multiple criteria with imprecise information, it is deliberated as an uncertain multicriteria decision‐making (MCDM) problem. The Pythagorean fuzzy set (PFS) is an important and effective way to tackle the uncertainty present in real‐life decision‐making problems. To select a suitable conversion technology from a set of options and upgrade the ARs‐to‐energy industries, the present study develops a combined approach to PFSs based on weighted discrimination‐based approximation (WDBA). This method extends the classical WDBA approach using an improved score function and discrimination measure within the PFS context, to evaluate MCDM problems with partial information on the criteria weights. To estimate the weights of the unknown attributes, a score function‐based linear programming model is developed. A new ranking method is extended to grade the options using the proposed discrimination measure within the PFS environment. Further, a case study assessing ARs‐to‐energy conversion technologies is conducted to illustrate the practicality and feasibility of this method. A comparative analysis shows that the approach developed is more effective and proficient in facilitating decision experts' selection of desirable BETs for ARs.

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“…There, we presented interesting applications of this concept in Pattern Recognition and Decision Theory. A similar generalization have been done for hesitant fuzzy sets in [16]. Moreover, we have been able to use the divergences to measure the fuzziness of a fuzzy set by comparing it with the closest crisp set and conversely, we have used fuzziness measures to define a divergence measure [22].…”

Section: Divergence Measuresmentioning

confidence: 99%

Divergence Measures: From Uncertainty to Imprecision

Montes¹,

Díaz²,

Martinetti³

2018

Studies in Systems, Decision and Control

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The link between information theory and fuzzy logic has been proven in several previous papers. From this starting point, we propose here a review about the concept of divergence measures, which was proposed as a tool for comparing two fuzzy sets. The initial definition comes from the ideas behind the classical concept of divergence between two probability distributions. Following a path similar to the one considered to obtain fuzziness measures from uncertainty measures, we are able to define fuzzy divergences. Apart from that, some possible generalizations are considered.Summary. *The link between information theory and fuzzy logic has been proven in several previous papers. From this starting point, we propose here a review about the concept of divergence measures, which was proposed as a tool for comparing two fuzzy sets. The initial definition comes from the ideas behind the classical concept of divergence between two probability distributions. Following a path similar to the one considered to obtain fuzziness measures from uncertainty measures, we are able to define the fuzzy divergences. Apart from that, some possible generalizations are considered.

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Divergence measures on hesitant fuzzy sets

Cited by 16 publications

References 18 publications

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

Pythagorean fuzzy weighted discrimination‐based approximation approach to the assessment of sustainable bioenergy technologies for agricultural residues

Divergence Measures: From Uncertainty to Imprecision

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