Neural network to develop sizing systems for production and logistics via technology innovation in Taiwan

  • Authors:
  • Chih-Hung Hsu;Cheng-Yueh Tsai;Tzu-Yuan Lee

  • Affiliations:
  • Department of Industrial Engineering and Management, Hsiuping Institute of Technology, Taiwan, R.O.C.;Department of Marketing and Logistics Management, Far East University, Taiwan, R.O.C.;Department of Industrial Engineering and Management, Hsiuping Institute of Technology, Taiwan, R.O.C.

  • Venue:
  • AIC'10/BEBI'10 Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informatics
  • Year:
  • 2010

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Abstract

Human body type classifications are very crucial issue, play an even important role for physiology, medical treatment, sports talent and garment production and logistics. The extraction of knowledge from large database has been successfully applied in a number of advanced fields by data mining. However, little research has been done in the area of identifying the significant rules of human body types, using data mining. The goal of this study was to identify the significant rules of human body types from the anthropometric data of adult males, using the neural network-based data mining procedure. Certain advantages may be observed when the significant rules are identified, using the neural network-based data mining procedure. Body types could be accurately classified for physiology, medical treatment, sports talent and garment manufacturing according the newly classification rules. The results of this study can provide an effective procedure of identifying the significant rules for classifying human body type to satisfy the demands of garment production and logistics.