Generalized evidence theory

Deng, Yong

doi:10.1007/s10489-015-0661-2

Cited by 249 publications

(200 citation statements)

References 65 publications

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“…Research has explored the statistical physics of games such as the Prisoner's Dilemma or the Snowdrift Game played out on lattices [420][421][422][423], subsequently expanded to networks [424][425][426][427][428][429][430][431]. Likewise, game theoretical concepts have been applied to vaccination decisions on networks [432][433][434][435].…”

Section: Game Theoretical Modelsmentioning

confidence: 99%

Statistical physics of vaccination

et al. 2016

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Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination-one of the most important preventive measures of modern times-is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.

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Section: Game Theoretical Modelsmentioning

confidence: 99%

Statistical physics of vaccination

et al. 2016

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“…Although D-S theory has lots of advantages, it will be invalid when highly conflicting evidences are combined and generate counterintuitive results [19][20][21]. To solve such a problem, two primary methodologies are popular.…”

Section: Introductionmentioning

confidence: 99%

Weighted Evidence Combination Based on Distance of Evidence and Entropy Function

Wang

Xiao

Deng

et al. 2016

International Journal of Distributed Sensor Networks

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Conflict management in Dempster-Shafer theory (D-S theory) is a hot topic in information fusion. In this paper, a new weighted evidence combination on the basis of the distance between evidence and entropy function is presented. The proposed approach is identified as two procedures. First, the weight is determined based on the distance of evidence. Then, the obtained weight value in the first step is modified by making advantage of Deng entropy function. Our proposed method can efficiently cope with high conflicting evidences with better performance of convergence. A numerical example is provided to demonstrate that the proposed method is reasonable and efficient in the end.

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“…It should also be noted that the conflict in D-S evidence theory is an open issue. Many methods have been proposed to address this issue [33,44].…”

Section: Dempster-shafer Evidence Theorymentioning

confidence: 99%

“…Herein, it is worth noting that the key issue of network security risk assessment is how to deal with the uncertainty information. Many solutions such as fuzzy sets theory [26][27][28], rough sets theory [29], possibility theory [30] and D-S evidence theory [31][32][33][34] can be applied to address the problem.…”

Section: Introductionmentioning

confidence: 99%

A Novel Network Security Risk Assessment Approach by Combining Subjective and Objective Weights under Uncertainty

et al. 2018

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Nowadays, computer networks are playing a more and more important role in people's daily lives. Meanwhile, the security of computer networks has also attracted widespread concern. However, up to now, there is no universal and effective assessment approach for computer network security. Therefore, a novel network security risk assessment approach by combining subjective and objective weights under uncertainty is proposed. In the proposed evaluation approach, the uncertainty of evaluation data is taken into account, which is translated into objective weights through an uncertainty measure. By combining the subjective weights of evaluation criteria and the objective weights of evaluation data, the final weights can be obtained. Then, Dempster-Shafer (D-S) evidence theory and pignistic probability transformation (PPT) are employed to derive a consensus decision for the degree of the network security risk. Two illustrative examples are given to show the efficiency of the proposed approach. This approach of risk assessment, which combines subjective and objective weights, can not only effectively evaluate computer network security, but also be widely used in decision-making.

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Generalized evidence theory

Cited by 249 publications

References 65 publications

Statistical physics of vaccination

Statistical physics of vaccination

Weighted Evidence Combination Based on Distance of Evidence and Entropy Function

A Novel Network Security Risk Assessment Approach by Combining Subjective and Objective Weights under Uncertainty

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