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Article type: Research Article
Authors: Zhen, Zhoua; b | Runtong, Zhangb; * | Yan, Pena | Yihong, Ronga | jie, Wanga
Affiliations: [a] School of Management, Capital Normal University, Beijing, China | [b] School of Economics and Management, Beijing Jiaotong University, Beijing, China
Correspondence: [*] Corresponding author. Zhang Runtong, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China. Tel.: +86(010) 84766681; E-mails: rtzhang@bjtu.edu.cn, jiucun2006@hotmail.com.
Abstract: Decision problems usually involve two important sources of uncertainty: randomness and fuzziness in real life. In this paper a mathematical model is developed to deal with dynamic Bayesian decision problems affected by uncertainties. The model can handle multi-step uncertainty decision problems involving randomness and fuzziness by a valuation-based system. The method uses linguistic variables to assess probabilities in the real-valued case, so a defuzzification method for the linguistic probability based on the concept of probability measure of fuzzy events is proposed. The decision valuations are described by triangular fuzzy sets. A fuzzy marginalization method based on fuzzy value comparison is proposed in the FVBS. A real world application example is provided to illustrate the method.
Keywords: Fuzzy sets, valuation-based system, uncertainty modelling, bayesian decision
DOI: 10.3233/IFS-152002
Journal: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2319-2329, 2016
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