Comparative study between radial basis function and polynomial of support vector regression in predicting flood

Comparative study between radial basis function and polynomial of support vector regression in predicting flood

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主要作者: Azhari , Farhana
格式: Thesis
出版: 2010
主题:
QA75 Electronic computers
Computer science
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id my-utm-ep.16326
record_format uketd_dc
spelling my-utm-ep.163262011-10-24T08:39:52Z Comparative study between radial basis function and polynomial of support vector regression in predicting flood 2010-00 Azhari , Farhana QA75 Electronic computers. Computer science 2010-00 Thesis http://eprints.utm.my/id/eprint/16326/ masters 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 QA75 Electronic computers
Computer science
spellingShingle QA75 Electronic computers
Computer science
Azhari , Farhana
Comparative study between radial basis function and polynomial of support vector regression in predicting flood
description
format Thesis
qualification_level Master's degree
author Azhari , Farhana
author_facet Azhari , Farhana
author_sort Azhari , Farhana
title Comparative study between radial basis function and polynomial of support vector regression in predicting flood
title_short Comparative study between radial basis function and polynomial of support vector regression in predicting flood
title_full Comparative study between radial basis function and polynomial of support vector regression in predicting flood
title_fullStr Comparative study between radial basis function and polynomial of support vector regression in predicting flood
title_full_unstemmed Comparative study between radial basis function and polynomial of support vector regression in predicting flood
title_sort comparative study between radial basis function and polynomial of support vector regression in predicting flood
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department Faculty of Computer Science and Information System
publishDate 2010
_version_ 1747815016412741632

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