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Issue title: Fuzzy Logic based Decision Making
Guest editors: Erik Maehle, Norbert Stoll and Chao-Hsien Chu
Article type: Research Article
Authors: Xu, Ronglong* | Zhang, Jing
Affiliations: Weifang University, Shandong 261000, China
Correspondence: [*] Corresponding author: Ronglong Xu, Weifang University, Shandong 261000, China. E-mail: [email protected].
Abstract: Enterprise information construction is the most effective way to improve the efficiency of process enterprises. Information integration technology is the key to implementing enterprise information. At the same time, fault diagnosis is also the technical focus of enterprise information. The fault diagnosis technology based on artificial intelligence method and the remote fault diagnosis technology based on B/S mode open up a new field for the research and application of fault diagnosis technology. When a certain mode, the output maximum value F n of the neural network is close to 0, and other values Smaller, both close to 0.1, then the system can be considered F n failure. Practice has proved that if there are enough training samples, the network has a strong diagnostic function to determine the correct rate of 96% or more, indicating that the network training effect is good and meets the diagnostic requirements.
Keywords: B/S, remote machinery, fault diagnosis
DOI: 10.3233/JCM-191049
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. S1, pp. 341-347, 2019
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