[1]FENG Zhiqiang,HAN Junfeng,HUANG Weiming,et al.Decision-making for welding process based on similarity-modified relation inference[J].CAAI Transactions on Intelligent Systems,2020,15(5):880-887.[doi:10.11992/tis.201901005]
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Decision-making for welding process based on similarity-modified relation inference

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 15 Number of periods: 2020 5 Page number: 880-887 Column: 学术论文—智能系统 Public date: 2020-09-05
Title:
Decision-making for welding process based on similarity-modified relation inference
Author(s):
FENG Zhiqiang1;  HAN Junfeng1; 2;  HUANG Weiming2;  LIU Cungen1; 3;  GAN Lu4;  HAN Xiangxi1;  JIAO Ziquan1
1. College of Mechanical and Marine Engineering, Beibu Gulf University, Qinzhou 535011, China;
2. College of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China;
3. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;
4. Advanced Connection Technology and Automation Equipment Research Laboratory, Shanghai Institute of Shipbuilding Technology, Shanghai 200032, China
Keywords:
approximate reasoning; similarity measure; nearness direction; modified relation; t-norm; modification relationship; translation operator; welding code parameters
CLC:
TP181
DOI:
10.11992/tis.201901005
Abstract:
Based on the analysis of the characteristics of compositional relation inference and existing similarity reasoning, an approximate reasoning pattern is proposed, which combines the similarity measure and nearness direction to generate a modified (or induced) fuzzy relation. By introducing the function of nearness direction between fuzzy concepts, expansion-typed and reduction-typed modification operators are constructed. Accordingly, a general expression of the reasoning model is given, and the selection of some modification and translation operators for constructing fuzzy relations is discussed. The proposed method is applied to the decision-making of welding process parameters and determining reasonable parameters of welding codes with a given penetration depth. The experimental results show that the reasoning model has high computational accuracy, which will help in the accurate output results of approximate reasoning to every change in the input fact.
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