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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: Ruan, Kuna | Li, Yuanb; *
Affiliations: [a] School of P.E., Shandong Yingcai University, Jinan Shandong, China | [b] School of P.E., Shandong University, Jinan Shandong, China
Correspondence: [*] Corresponding author. Yuan Li, School of P.E., Shandong University, Jinan Shandong, China. E-mail: sdtyxyliyuan@sdu.edu.cn.
Abstract: Using the theoretical knowledge of ergonomics, physiology, and psychology, carried out the humanized design of human body adaptive sports equipment; using the theoretical knowledge of modeling, color, material science and other related disciplines, proposed the human body adaptive sports equipment Humanized design method. Aiming at the fuzziness of the industrial design of human adaptive sports equipment, fuzzy mathematics theory is used as an analysis tool, combined with the actual characteristics of the industrial design of human adaptive sports equipment, focusing on the nature of industrial design under fuzzy theory. Comprehensive analysis and understanding of design-related factors, and the introduction of expert survey method in the case of no basic data source in innovative design, to obtain the weight value of single factor influence, this will help designers grasp the main contradiction, achieve a targeted, and Solve key problems with higher efficiency. Subsequent use of fuzzy mathematics tools to put forward a quantitative index for the selection of options, which will help analyze the pros and cons of the various options, so as to provide a reliable reference for decision makers. This method makes up for the shortcomings of traditional methods in the process of design factor analysis and program selection.
Keywords: Human body adaptation, sports equipment, industrial design, fuzzy mathematics
DOI: 10.3233/JIFS-189449
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6103-6112, 2021
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