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Improving software reliability model selection ranking using computational intelligence parameter estimation

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Main Author: Mohd Adham Isa Dayang Nor, Ong Liang Fuh
Format: Article
Published: 2018
Online Access:http://eprints.utm.my/id/eprint/82064/
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id my.utm.82064
record_format eprints
spelling my.utm.820642019-09-30T09:00:46Z http://eprints.utm.my/id/eprint/82064/ Improving software reliability model selection ranking using computational intelligence parameter estimation Mohd Adham Isa Dayang Nor, Ong Liang Fuh 2018 Article PeerReviewed Mohd Adham Isa Dayang Nor, Ong Liang Fuh (2018) Improving software reliability model selection ranking using computational intelligence parameter estimation. INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND TECHNOLOGY .
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
format Article
author Mohd Adham Isa Dayang Nor, Ong Liang Fuh
spellingShingle Mohd Adham Isa Dayang Nor, Ong Liang Fuh
Improving software reliability model selection ranking using computational intelligence parameter estimation
author_facet Mohd Adham Isa Dayang Nor, Ong Liang Fuh
author_sort Mohd Adham Isa Dayang Nor, Ong Liang Fuh
title Improving software reliability model selection ranking using computational intelligence parameter estimation
title_short Improving software reliability model selection ranking using computational intelligence parameter estimation
title_full Improving software reliability model selection ranking using computational intelligence parameter estimation
title_fullStr Improving software reliability model selection ranking using computational intelligence parameter estimation
title_full_unstemmed Improving software reliability model selection ranking using computational intelligence parameter estimation
title_sort improving software reliability model selection ranking using computational intelligence parameter estimation
publishDate 2018
url http://eprints.utm.my/id/eprint/82064/
_version_ 1651866401985527808
score 13.18916

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