Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets

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Bibliographic Details
Main Author: Ayinde, Folorunso Olufemi
Format: Thesis
Published: 2011
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id my-utm-ep.28493
record_format uketd_dc
spelling my-utm-ep.284932015-03-10T03:55:22Z Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets 2011 Ayinde, Folorunso Olufemi Unspecified 2011 Thesis http://eprints.utm.my/id/eprint/28493/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:67988?site_name=Restricted Repository phd doctoral Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
topic Unspecified
spellingShingle Unspecified
Ayinde, Folorunso Olufemi
Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
description
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Ayinde, Folorunso Olufemi
author_facet Ayinde, Folorunso Olufemi
author_sort Ayinde, Folorunso Olufemi
title Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
title_short Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
title_full Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
title_fullStr Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
title_full_unstemmed Improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
title_sort improved data normalisation and dimensionality reduction algorithms for visualisation of pipeline sensor datasets
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department Faculty of Computer Science and Information System
publishDate 2011
_version_ 1747815666802491392