Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/8187
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSamir, Nariman
dc.contributor.authorSupervisor - Mohamed Elhafiz Mustafa
dc.date.accessioned2014-11-23T11:19:36Z
dc.date.available2014-11-23T11:19:36Z
dc.date.issued2014-09-22
dc.identifier.citationSamir, Nariman. Clustering Technique For Analyzing Garment Sizing Systems/ Nariman Samir؛ Mohamed Elhafiz Mustafa.-Khartoum : sudan university of science and technology,computer science,2014.-42p:ill;28cm.M.Sc.en_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/8187
dc.descriptionCDen_US
dc.description.abstractIn garment production engineering, sizing system plays an important role for manufacturing of clothing. The standards for defining the size status are a critical issue. Locating the right garment size for a customer depends on the label as an interface. The intend in of this research is to use data mining technique (clustering) to access the suitability of the standard sizing system to Sudanese (men shirt & men trousers). The data set used in the research was collected for the men’s age ranges between 25 and 66 years. This research is comparing international standard sizing system (XS, S, M, L, XL, 2XL, 3XL), with our data set. There are 3 experiments have been performed to find the distribution of Sudanese (male) sizes. The results show that: The size 3XL does almost not exist among the data and the majority of Sudanese are in the S sizes (36% for shirt) and L sizes (43% for trouser).en_US
dc.description.sponsorshipSudan University of Science and Technologyen_US
dc.language.isoen_USen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectGarment Sizing Systemsen_US
dc.subjectClustering Techniqueen_US
dc.subjectdata miningen_US
dc.subjectclusteringen_US
dc.titleClustering Technique For Analyzing Garment Sizing Systemsen_US
dc.title.alternativeتقنيات العنقدة لتحليل أنظمة قياسات الملابسen_US
dc.typeThesisen_US
Appears in Collections:Masters Dissertations : Computer Science and Information Technology

Files in This Item:
File Description SizeFormat 
the Title and abstract.pdf137.63 kBAdobe PDFView/Open
the Research.pdf408.58 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.