A data-driven group emergency decision-making method based on interval-valued intuitionistic hesitant fuzzy sets and its application in COVID-19 pandemic

Du, Kang; Fan, Ruguo; Wang, Yuanyuan; Wang, Dongxue; Qian, Rourou; Zhu, Bi‐Xue

doi:10.1016/j.asoc.2023.110213

Cited by 15 publications

(3 citation statements)

References 59 publications

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“…(3) Utilizing the feature weights 𝜆 𝑗 (𝑗 = 1, ⋯ ,3) obtained in section 4.1, calculate the summation of weighted positive ideal and negative ideal distances 𝑆𝑃 𝑖 and 𝑆𝑁 𝑖 of each sample point, in accordance with Eqs. ( 20) and (21).…”

Section: Deriving Sample Point Weights Among Sliding Windowmentioning

confidence: 99%

“…On the other hand, the BM operator, proposed by Bonferroni [20], effectively captures the correlation between input variables among various aggregation operators. The BM operator has drawn the attention of researchers, leading to considerable research efforts [21][22]. Recently, Xu and Yager [23] expanded the BM operator to information integration in IFS environment.…”

Section: Introductionmentioning

confidence: 99%

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A Warning Feedback Model Based on Online Learning Engagement Evaluation Under Interval-valued q-rung Orthopair Fuzzy

Wan,

Xie,

Pierre

2023

Preprint

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When real-time detection indicates a low level of student engagement in online classrooms, selecting an appropriate time for feedback can enhance learner engagement. To address this issue, this study proposes an Interval-valued q-rung orthopair fuzzy warning feedback model based on the evaluation of online learning engagement. The designed warning feedback model utilizes a sliding window to capture the linguistic evaluation results of facial expressions, eye gaze, and limb states of online learners. By employing the developed IVq-ROFWDBM operator, as well as feature weight derivation and sample point weight derivation methods, the fuzzy comprehensive evaluation of sample points within the sliding window is conducted. When the evaluation result indicates low engagement, timely feedback is provided to the learners. The implementation of case studies demonstrates that the proposed warning feedback model can provide timely and effective feedback, avoiding the contradiction between excessive and untimely feedback. Comparative analysis results indicate that the proposed operator can obtain more accurate feedback outcomes.

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Section: Deriving Sample Point Weights Among Sliding Windowmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Warning Feedback Model Based on Online Learning Engagement Evaluation Under Interval-valued q-rung Orthopair Fuzzy

Wan,

Xie,

Pierre

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…De et al [33] extended the TOPSIS method to solve multiattribute decision-making problems with probabilistic IIHF decisions. Du et al [34] rendered a data-driven group decision-making method under the IIHF environment. Bhaumik et al [35] discussed a bimatrix game problem with hesitant interval-valued intuitionistic linguistic payoffs in the light of the prisoner's dilemmatic approach and applied it to portray the human trafficking problem.…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Programming Approach to Solving Interval-Valued Intuitionistic Hesitant Noncooperative Fuzzy Matrix Games

Karmakar,

Seikh

2024

Symmetry

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Initially, fuzzy sets and intuitionistic fuzzy sets were used to address real-world problems with imprecise data. Eventually, the notion of the hesitant fuzzy set was formulated to handle decision makers’ reluctance to accept asymmetric information. However, in certain scenarios, asymmetric information is gathered in terms of a possible range of acceptance and nonacceptance by players rather than specific values. Furthermore, decision makers exhibit some hesitancy regarding this information. In such a situation, all the aforementioned expansions of fuzzy sets are unable to accurately represent the scenario. The purpose of this article is to present asymmetric information situations in which the range of choices takes into account the hesitancy of players in accepting or not accepting information. To illustrate these problems, we develop matrix games that consider the payoffs of interval-valued intuitionistic hesitant fuzzy elements (IIHFEs). Dealing with these types of fuzzy programming problems requires a significant amount of effort. To solve these matrix games, we formulate two interval-valued intuitionistic hesitant fuzzy programming problems. Preserving the hesitant nature of the payoffs to determine the optimal strategies, these two problems are transformed into two nonlinear programming problems. This transformation involves using mathematical operations for IIHFEs. Here, we construct a novel aggregation operator of IIHFEs, viz., min-max operators of IIHFEs. This operator is suitable for applying the developed methodology. The cogency and applicability of the proposed methodology are verified through a numerical example based on the situation of conflict between hackers and defenders to prevent damage to cybersecurity. To validate the superiority of the proposed model along with the computed results, we provide comparisons with the existing models.

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A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network

Yang,

Zhang

2024

Complex Intell. Syst.

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A new intuitionistic fuzzy consensus reaching model is developed with multi-period public opinions and expert evaluation values in social network environment. First, the public opinions are obtained by using the crawler software and sentiment analysis technology is used to transform public opinions into intuitionistic fuzzy decision matrix in each period. Attribute weights are calculated by using the time attenuation factor and changes in public opinion. Second, the social trust relationship is modeled and incomplete social trust relationships are completed by using Archimedean t-norm. The expert weights are calculated by using the dynamic trust degree and similarity degree. Third, a consensus framework is proposed for multiple-period decision making problem, which coordinates conflicts between experts through dual feedback paths. The collective opinion scores are calculated by using weights of periods and attribute weights obtained from the word frequency of public opinions. The tourism attraction recommendation method is used to illustrate the proposed method.

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A data-driven group emergency decision-making method based on interval-valued intuitionistic hesitant fuzzy sets and its application in COVID-19 pandemic

Cited by 15 publications

References 59 publications

A Warning Feedback Model Based on Online Learning Engagement Evaluation Under Interval-valued q-rung Orthopair Fuzzy

A Warning Feedback Model Based on Online Learning Engagement Evaluation Under Interval-valued q-rung Orthopair Fuzzy

A Nonlinear Programming Approach to Solving Interval-Valued Intuitionistic Hesitant Noncooperative Fuzzy Matrix Games

A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network

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