JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2020, Vol. 55 ›› Issue (7): 67-80.doi: 10.6040/j.issn.1671-9352.0.2019.585

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Method of uncertain temporal event flow sequence reasoning based on multiple attribute decision making

ZHENG Huan-ke1, ZHANG Jing1,2,3*, YANG Ya-qi4, XIONG Mei-hui1   

  1. 1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, Yunnan, China;
    2. Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming 650500, Yunnan, China;
    3. Yunnan Xiaorun Technology Service Limited, Kunming 650500, Yunnan, China;
    4. Yunnan Administration for Market Regulation, Kunming 650228, Yunnan, China
  • Published:2020-07-08

Abstract: In the cyber-physical system, the scheduling sequence of uncertain temporal event flows has a single decision-making problem. To solve this problem, this paper firstly uses the advantage of D-S evidence theory in multi-evidence source probability fusion, considering the influence of multiple attributes such as event priority, deadline, urgency and event dependency, to construct a basic probability distribution model for fuzzy end time with multi-attribute features. Then, an association model with intuitionistic fuzzy sets and D-S evidence theory is established, and through this model, the membership and non-membership of the IFS at the fuzzy end time can be obtained. On this basis, negative temporal reasoning of IFS and correlation scoring function are used to derive the fuzzy start time probability score, and finally obtain the time series reasoning result, which is used to determine the uncertain temporal event flow scheduling order based on multi-attribute criterion. The experimental results show that when the number of events increases, the methods scheduling accuracy rate can keep more than 85%. And when the size of the fuzzy interval limit is expanded, the scheduling accuracy rate does not decrease more than 15%.

Key words: cyber-physical system, CPS scheduling, intuitionistic fuzzy sets, D-S evidence theory

CLC Number: 

  • TP311
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