The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 29-498
Full Name: CHIH-HUNG HSU
Position: Assistant Professor
Age: ON
Sex: Male
Address: No. 11 Gungye Road, Dali, Taichung County, 41249. Taiwan, R.O.C.
Country: TAIWAN
Tel: +886-938-837808
Tel prefix: +886-938-837808
Fax: +886-4-24961178
E-mail address: chhsu@mail.hit.edu.tw
Other E-mails: shuchihhung@yahoo.com.tw,l1212878@ms47.hinet.net
Title of the Paper: Mining the body features to develop sizing systems to improve business logistics and marketing using fuzzy clustering data mining
Authors as they appear in the Paper: Chih-Hung Hsu, Tzu-Yuan Lee, Hui-Ming Kuo
Email addresses of all the authors: chhsu@mail.hit.edu.tw,tylee@mail.hit.edu.tw,hmkuo@mail.stu.edu.tw
Number of paper pages: 10
Abstract: Business logistics have played an important role of business operations of procurement, purchasing, inventory, warehousing, distribution, transportation, customer support, financial and human resources. Human body type classifications are also very crucial issue for garment manufacturing. Data mining has been widely used in many fields. But, there is lack of research in the area of establishing of garment-sizing systems for business logistics. This research aims to establish sizing systems of body types from the anthropometric data of females by using a fuzzy clustering-based data mining approach. Certain advantages may be observed when the sizing systems are established, using fuzzy clustering-based data mining procedure. Body types could be accurately classified for garment production according the newly the sizing systems. This approach is found to be effective in processing the anthropometric data, and obtaining regular rules for the development of sizing syste!
ms. The results of this study can provide an effective procedure of identifying the clusters of human body type to establish the sizing systems for integrating logistics operations internally with different functions inside the organization and also externally with business partners.
Keywords: Data mining; Fuzzy clustering; Sizing systems; Business logistics.
EXTENSION of the file: .pdf
Special (Invited) Session: Applying Fuzzy Theory based Data Mining to Establish the Female Sizing Systems for Garment Production
Organizer of the Session: 613-468
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