A hesitant fuzzy model of computational trust considering hesitancy, vagueness and uncertainty

Ashtiani, Mehrdad; Azgomi, Mohammad Abdollahi

doi:10.1016/j.asoc.2016.01.023

Cited by 33 publications

(9 citation statements)

References 38 publications

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“…Next, Thakur, Thakur, Singh and Engineering [96] proposed some new aggregation operators for HFSs. Ashtiani and Azgomi [97] suggested an innovative hesitant fuzzy-based computational trust model deal with the vagueness and hesitancy of trust MCDM problems. Faizi et al.…”

Section: Methodsmentioning

confidence: 99%

A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak

Mardani

Saraji

Mishra³

et al. 2020

Applied Soft Computing

130

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In recent years, Digital Technologies (DTs) are becoming an inseparable part of human lives. Thus, many scholars have conducted research to develop new tools and applications. Processing information, usually in the form of binary code, is the main task in DTs, which is happening through many devices, including computers, smartphones, robots, and applications. Surprisingly, the role of DTs has been highlighted in people’s life due to the COVID-19 pandemic. There are several different challenges to implement and intervene in DTs during the COVID-19 outbreak; therefore, the present study extended a new fuzzy approach under Hesitant Fuzzy Set (HFS) approach using Stepwise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) method to evaluate and rank the critical challenges of DTs intervention to control the COVID-19 outbreak. In this regard, a comprehensive survey using literature and in-depth interviews have been carried out to identify the challenges under the SWOT (Strengths, Weaknesses, Opportunities, Threats) framework. Moreover, the SWARA procedure is applied to analyze and assess the challenges to DTs intervention during the COVID-19 outbreak, and the WASPAS approach is utilized to rank the DTs under hesitant fuzzy sets. Further, to demonstrate the efficacy and practicability of the developed framework, an illustrative case study has been analyzed. The results of this study found that Health Information Systems (HIS) was ranked as the first factor among other factors followed by a lack of digital knowledge, digital stratification, economic interventions, lack of reliable data, and cost inefficiency In conclusion, to confirm the steadiness and strength of the proposed framework, the obtained outputs are compared with other methods.

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Section: Methodsmentioning

confidence: 99%

A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak

Mardani

Saraji

Mishra³

et al. 2020

Applied Soft Computing

130

View full text Add to dashboard Cite

show abstract

“…It permits the membership value of an element to a set being represented by several possible values between 0 and 1. Since the HFS was proposed, it has been studied in depth by scholars (Rodríguez et al 2016;Onar et al 2016;Liu et al 2015;Liao, Xu 2013;Alcantud et al 2016;Ashtiani, Azgomi 2016;Li et al 2015;Meng, Chen 2015;Zhu, Xu. 2014).…”

Section: Introductionmentioning

confidence: 99%

Hfmadm Method Based on Nondimensionalization and Its Application in the Evaluation of Inclusive Growth

Wang

Hetzler

2017

Journal of Business Economics and Management

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Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (hfes) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method.

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“…Besides a variety of operations, properties and fuzzy measures on HFSs, the hesitant fuzzy sets has shown its advantages in such the real fields as decision-making [3,4,6,[16][17][18][19][20][21], feature selection [22], pattern recognition [13], cluster analysis [15,16] and linguistic computing [23][24][25]. He et al [17] first introduced the expected value and the geometric average value of hesitant multiplicative element (HME) to group decision making problems.…”

Section: Introductionmentioning

confidence: 99%

“…Zhang et al [20] proposed an interval programming method for solving MAGDM problems with hesitant fuzzy alternatives based on LINMAP. Ashtiani and Azgomi [21] proposed a hesitant fuzzy multi-criteria decision making based computational trust model capable of taking into account the fundamental building blocks corresponding to the concept of trust. Ebrahimpour and Eftekhari [22] proposed an innovative method to deal with feature subset selection with HFSs based on Maximum Relevancy and Minimum Redundancy approach.…”

Section: Introductionmentioning

confidence: 99%

Grey Relational Analysis for Hesitant Fuzzy Sets and Interval-Valued Hesitant Fuzzy Sets with Applications to MADM Problems

Guan¹,

Sun²,

Yi³

et al. 2017

Preprint

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Quantitative and qualitative fuzzy measures have been proposed to hesitant fuzzy sets 9 (HFSs) from different points. However, few of the existing HFSs fuzzy measures refer to the grey 10 relational analysis (GRA) theory. Actually, the GRA theory is very useful in the fuzzy measure 11 domain, which has been developed for such the intuitionistic fuzzy sets. Therefore, in this paper, 12we apply the GRA theory to the HFSs and interval-valued hesitant fuzzy sets (IVHFS) domain. We

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A hesitant fuzzy model of computational trust considering hesitancy, vagueness and uncertainty

Cited by 33 publications

References 38 publications

A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak

A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak

Hfmadm Method Based on Nondimensionalization and Its Application in the Evaluation of Inclusive Growth

Grey Relational Analysis for Hesitant Fuzzy Sets and Interval-Valued Hesitant Fuzzy Sets with Applications to MADM Problems

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