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Issue title: Meta-Heuristic Techniques for Solving Computational Engineering Problems: Challenges and New Research Directions
Guest editors: Suresh Chandra Satapathy, Rashmi Agrawal and Vicente García Díaz
Article type: Research Article
Authors: Weiqi, Wanga; * | Yanmei, Zhangb | Shouyi, Sunc | Guoqiang, Xiaoc
Affiliations: [a] China University of Geosciences (Wuhan), Wuhan, Hubei, China | [b] Investment Promotion Bureau of Shuicheng County Liupanshui, Guizhou, China | [c] Guizhou faer Coal Industry Co., Ltd, Liupanshui, Guizhou, China
Correspondence: [*] Corresponding author. Wang Weiqi, China University of Geosciences (Wuhan), Wuhan, Hubei, China. E-mail: zhanghappy56@qq.com.
Abstract: A dynamic diagnosis system of mine safety based on multi-data fusion is designed by combining the advantages of cloud computing and the Internet of things. The system’s framework is built with a three-tier model, and the construction of the cloud computing service platform provides essential support for mass data storage, processing, and security diagnosis reasoning. Simultaneously, using the relational database SQL Server 2017 and the object-oriented language C# to complete the design of an expert knowledge base and reasoning mechanism, and establish the diagnostic scoring system in the way of weighted sum. Therefore, based on the logical matching and reasoning between the collected data and the safety rules, the dynamic diagnosis of mine safety is realized.
Keywords: Cloud computing, internet of things, expert knowledge base, reasoning mechanism
DOI: 10.3233/JIFS-189423
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5837-5844, 2021
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