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Research on Evaluation Method Based on Modified Buckley Decision Making and Bayesian Network
Author(s) -
Nengpu Yang,
Mei Han,
Shiyong Chen,
Xiaohua Liu,
Liujiang Kang
Publication year - 2015
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2015/489207
Subject(s) - computer science , bayesian network , criticality , reliability (semiconductor) , objectivity (philosophy) , bayesian probability , reliability engineering , process (computing) , data mining , fuzzy logic , field (mathematics) , core (optical fiber) , operations research , risk analysis (engineering) , machine learning , artificial intelligence , engineering , mathematics , medicine , telecommunications , power (physics) , philosophy , physics , epistemology , quantum mechanics , nuclear physics , pure mathematics , operating system
This work presents a novel evaluation method, which can be applied in the field of risk assessment, project management, cause analysis, and so forth. Two core technologies are used in the method, namely, modified Buckley Decision Making and Bayesian Network. Based on the modified Buckley Decision Making, the fuzzy probabilities of element factors are calibrated. By the forward and backward calculation of Bayesian Network, the structure importance, probability importance, and criticality importance of each factor are calculated and discussed. A numerical example of risk evaluation for dangerous goods transport process is given to verify the method. The results indicate that the method can efficiently identify the weakest element factor. In addition, the method can improve the reliability and objectivity for evaluation

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