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Yefan Han

Datos Biográficos

ID9634182
NOMBREYefan Han
NOMBRESYefan
APELLIDOHan
FIRMAHAN Y
AFILIACIONESUniversity of Shanghai for Science and Technology
ORCID0000-0002-3736-978X
VERIFICADOSí
TOTAL DE OBRAS3
TOTAL DE CITAS0
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2021
AÑO MÁS RECIENTE DE PUBLICACIÓN2022
ÍNDICE H0
  • A Robust Minimum-Cost Consensus Model With Uncertain Aggregation Weights Based on Data-Driven Method

    Open Access•Yefan Han, Ying Ji et al.•ARTICLE•IEEE Transactions on Computational…•2022

    Due to the existence of cognitive bias, it is difficult to accurately obtain the decision-makers’ weights in the aggregating process, which leads to great fluctuations in the optimal decision-making. Therefore, the purpose of this article is to establish a data-driven robust cost consensus model induced by uncertain weights to deal with the adverse effects of uncertainty in the aggregating process. First, the probability density function of the u…

  • New Insights Into the Social Rumor Characteristics During the Covid-19 Pandemic in China

    Open Access•Wei Lv, Wennan Zhou et al.•ARTICLE•Frontiers in Public Health•2022

    Background: In the early stage of the COVID-19 outbreak in China, several social rumors in the form of false news, conspiracy theories, and magical cures had ever been shared and spread among the general public at an alarming rate, causing public panic and increasing the complexity and difficulty of social management. Therefore, this study aims to reveal the characteristics and the driving factors of the social rumors during the COVID-19 pandemic…

  • Consensus Modeling with Asymmetric Cost Based on Data-Driven Robust Optimization

    Open Access•Shaojian Qu, Yefan Han et al.•ARTICLE•Group Decision and Negotiation•2021

Sin obras prominentes en esta página.

  • Consensus Modeling with Asymmetric Cost Based on Data-Driven Robust Optimization

    Open Access•Shaojian Qu, Yefan Han et al.•ARTICLE•Group Decision and Negotiation•2021

  • A Robust Minimum-Cost Consensus Model With Uncertain Aggregation Weights Based on Data-Driven Method

    Open Access•Yefan Han, Ying Ji et al.•ARTICLE•IEEE Transactions on Computational…•2022

    Due to the existence of cognitive bias, it is difficult to accurately obtain the decision-makers’ weights in the aggregating process, which leads to great fluctuations in the optimal decision-making. Therefore, the purpose of this article is to establish a data-driven robust cost consensus model induced by uncertain weights to deal with the adverse effects of uncertainty in the aggregating process. First, the probability density function of the u…

  • New Insights Into the Social Rumor Characteristics During the Covid-19 Pandemic in China

    Open Access•Wei Lv, Wennan Zhou et al.•ARTICLE•Frontiers in Public Health•2022

    Background: In the early stage of the COVID-19 outbreak in China, several social rumors in the form of false news, conspiracy theories, and magical cures had ever been shared and spread among the general public at an alarming rate, causing public panic and increasing the complexity and difficulty of social management. Therefore, this study aims to reveal the characteristics and the driving factors of the social rumors during the COVID-19 pandemic…

Computer Science (3 obras) · Fuzzy Systems and Optimization (2 obras) · Mathematical optimization (2 obras) · Mathematics (2 obras) · Multi-Criteria Decision Making (2 obras) · Algorithm (1 obras) · Chemistry (1 obras) · China (1 obras) · Climate Change Communication and Perception (1 obras) · Complex Network Analysis Techniques (1 obras)

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