A new evaluation method based on D–S generalized fuzzy soft sets and its application in medical diagnosis problem

Xiao, Zhi; Yang, Xianglei; Qing, Niu; Dong, Yuanxiang; Гонг, Ке; Xia, Sisi; Pang, Ying Han

doi:10.1016/j.apm.2011.11.049

Cited by 36 publications

(10 citation statements)

References 32 publications

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“…Jiang et al [ 59 ] presented an adjustable approach to IFSSs-based decision making by using level soft sets of IFSSs. To deal with the problems of subjective evaluation and uncertain knowledge, Xiao et al [ 60 ] proposed an evaluation method based on GFSSs and its application in medical diagnosis problem. They also [ 61 ] extended classical SSs to trapezoidal fuzzy soft sets (TFSSs) and applied them to MCDM problems.…”

Section: Introductionmentioning

confidence: 99%

Hesitant Fuzzy Soft Sets with Application in Multicriteria Group Decision Making Problems

Wang

Chen

2015

The Scientific World Journal

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Soft sets have been regarded as a useful mathematical tool to deal with uncertainty. In recent years, many scholars have shown an intense interest in soft sets and extended standard soft sets to intuitionistic fuzzy soft sets, interval-valued fuzzy soft sets, and generalized fuzzy soft sets. In this paper, hesitant fuzzy soft sets are defined by combining fuzzy soft sets with hesitant fuzzy sets. And some operations on hesitant fuzzy soft sets based on Archimedean t-norm and Archimedean t-conorm are defined. Besides, four aggregation operations, such as the HFSWA, HFSWG, GHFSWA, and GHFSWG operators, are given. Based on these operators, a multicriteria group decision making approach with hesitant fuzzy soft sets is also proposed. To demonstrate its accuracy and applicability, this approach is finally employed to calculate a numerical example.

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Section: Introductionmentioning

confidence: 99%

Hesitant Fuzzy Soft Sets with Application in Multicriteria Group Decision Making Problems

Wang

Chen

2015

The Scientific World Journal

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“…Neog and Sut (2011) introduced a matrix representation of fuzzy soft set and extended Sanchez's approach for medical diagnosis using the notion of fuzzy soft complement. Xiao et al (2012) proposed the concept of D-S generalized fuzzy soft sets by combining Dempster-Shafer theory of evidence and generalized fuzzy soft sets. A new method of evaluation based on D-S generalized fuzzy soft sets was presented and applied to the medical diagnosis.…”

Section: Introductionmentioning

confidence: 99%

HIFCF: An effective hybrid model between picture fuzzy clustering and intuitionistic fuzzy recommender systems for medical diagnosis

Thong

Sơn

2015

Expert Systems with Applications

177

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“…Xiao et al . [ 44 ] proposed the concept of D-S generalized fuzzy soft set by combining Dempster-Shafer theory of evidence and generalized fuzzy soft sets. Gong et al .…”

Section: Introductionmentioning

confidence: 99%

An Efficient Soft Set-Based Approach for Conflict Analysis

et al. 2016

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Conflict analysis has been used as an important tool in economic, business, governmental and political dispute, games, management negotiations, military operations and etc. There are many mathematical formal models have been proposed to handle conflict situations and one of the most popular is rough set theory. With the ability to handle vagueness from the conflict data set, rough set theory has been successfully used. However, computational time is still an issue when determining the certainty, coverage, and strength of conflict situations. In this paper, we present an alternative approach to handle conflict situations, based on some ideas using soft set theory. The novelty of the proposed approach is that, unlike in rough set theory that uses decision rules, it is based on the concept of co-occurrence of parameters in soft set theory. We illustrate the proposed approach by means of a tutorial example of voting analysis in conflict situations. Furthermore, we elaborate the proposed approach on real world dataset of political conflict in Indonesian Parliament. We show that, the proposed approach achieves lower computational time as compared to rough set theory of up to 3.9%.

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A new evaluation method based on D–S generalized fuzzy soft sets and its application in medical diagnosis problem

Cited by 36 publications

References 32 publications

Hesitant Fuzzy Soft Sets with Application in Multicriteria Group Decision Making Problems

Hesitant Fuzzy Soft Sets with Application in Multicriteria Group Decision Making Problems

HIFCF: An effective hybrid model between picture fuzzy clustering and intuitionistic fuzzy recommender systems for medical diagnosis

An Efficient Soft Set-Based Approach for Conflict Analysis

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