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Belief functions and uncertainty management in networks and telecommunication

机译:网络和电信中的信念功能和不确定性管理

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摘要

In the last few years, Dempster-Shafer theory also known as Theory of Belief Functions (TBF) or Evidence theory has received growing attention in many fields of applications such as finance, technology, biomedicine, etc. This theory may be seen as a generalization framework of different instances such as probability, fuzzy sets, and possibility theories. Using Dempster-Shafer belief functions to express available information allows considering two kinds of uncertainty: aleatory uncertainty due to the variability of the variable of interest in the population and epistemic uncertainty due to a lack of knowledge on the state of the variable.
机译:在最近几年中,Dempster-Shafer理论(也称为信念函数理论(TBF)或证据理论)在金融,技术,生物医学等许多应用领域中受到越来越多的关注。该理论可以看作是一种概括。不同实例的框架,例如概率,模糊集和可能性理论。使用Dempster-Shafer信念函数表示可用信息可以考虑两种不确定性:由于人口中关注变量的可变性而导致的不确定性,以及由于对该变量的状态缺乏了解而导致的认知不确定性。

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  • 来源
    《Annales des Telecommunications》 |2014年第4期|131-133|共3页
  • 作者单位

    Department of Network & Telecommunication and LiSSi Laboratory-TincNET Team, University of Paris Est Creteil Val de Marne (UPEC), 122, rue Paul Armangot, 94400 Vitry sur Seine, France;

    COSYS-GRETTIA, IFSTTAR-French Institute of Science and Technology for Transport, Development and Networks, 14-20 Boulevard Newton, Cite Descartes, Champs sur Marne, 77447 Marne la Vallee Cedex 2, France;

    Guangdong Provincial Key Lab. of Petrochemical Equipment Fault Diagnosis, Guangdong University of Petrochemical Technology, No. 139, Guandu Erlu, Maonan, Maoming, Guangdong, China 525000;

    Rutgers Business School-Newark and New Brunswick, 1 Washington Park, Newark, NJ 07102, USA;

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