Data aggregation for capacity management

This thesis presents a methodology for data aggregation for capacity management. It is assumed that there are a very large number of products manufactured in a company and that every product is stored in the database with its standard unit per hour and attributes that uniquely specify each product....

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Bibliographic Details
Main Author:	Lee, Yong Woo
Other Authors:	Leon, V. Jorge
Format:	Others
Language:	en_US
Published:	Texas A&M University 2004
Subjects:	data aggregation capacity management data reduction classification
Online Access:	http://hdl.handle.net/1969.1/90

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spelling	ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-902013-01-08T10:37:11ZData aggregation for capacity managementLee, Yong Woodata aggregationcapacity managementdata reductionclassificationThis thesis presents a methodology for data aggregation for capacity management. It is assumed that there are a very large number of products manufactured in a company and that every product is stored in the database with its standard unit per hour and attributes that uniquely specify each product. The methodology aggregates products into families based on the standard units-per-hour and finds a subset of attributes that unambiguously identifies each family. Data reduction and classification are achieved using well-known multivariate statistical techniques such as cluster analysis, variable selection and discriminant analysis. The experimental results suggest that the efficacy of the proposed methodology is good in terms of data reduction.Texas A&M UniversityLeon, V. Jorge2004-09-30T01:41:56Z2004-09-30T01:41:56Z2003-052004-09-30T01:41:56ZElectronic Thesistext858806 bytes69716 byteselectronicapplication/pdftext/plainborn digitalhttp://hdl.handle.net/1969.1/90en_US
collection	NDLTD
language	en_US
format	Others
sources	NDLTD
topic	data aggregation capacity management data reduction classification
spellingShingle	data aggregation capacity management data reduction classification Lee, Yong Woo Data aggregation for capacity management
description	This thesis presents a methodology for data aggregation for capacity management. It is assumed that there are a very large number of products manufactured in a company and that every product is stored in the database with its standard unit per hour and attributes that uniquely specify each product. The methodology aggregates products into families based on the standard units-per-hour and finds a subset of attributes that unambiguously identifies each family. Data reduction and classification are achieved using well-known multivariate statistical techniques such as cluster analysis, variable selection and discriminant analysis. The experimental results suggest that the efficacy of the proposed methodology is good in terms of data reduction.
author2	Leon, V. Jorge
author_facet	Leon, V. Jorge Lee, Yong Woo
author	Lee, Yong Woo
author_sort	Lee, Yong Woo
title	Data aggregation for capacity management
title_short	Data aggregation for capacity management
title_full	Data aggregation for capacity management
title_fullStr	Data aggregation for capacity management
title_full_unstemmed	Data aggregation for capacity management
title_sort	data aggregation for capacity management
publisher	Texas A&M University
publishDate	2004
url	http://hdl.handle.net/1969.1/90
work_keys_str_mv	AT leeyongwoo dataaggregationforcapacitymanagement
_version_	1716503065508446208

Data aggregation for capacity management

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