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An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect

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Main Authors: Lo, M., Vijaya Kumar, S.D., Karuppanan, S., Ovinis, M.
Format: Article
Published: MDPI 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124343364&doi=10.3390%2fapp12031722&partnerID=40&md5=5fda8310cdc5a3a41c9ffd55640ffb8e
http://eprints.utp.edu.my/28678/
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spelling my.utp.eprints.286782022-03-07T12:54:59Z An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect Lo, M. Vijaya Kumar, S.D. Karuppanan, S. Ovinis, M. MDPI 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124343364&doi=10.3390%2fapp12031722&partnerID=40&md5=5fda8310cdc5a3a41c9ffd55640ffb8e Lo, M. and Vijaya Kumar, S.D. and Karuppanan, S. and Ovinis, M. (2022) An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect. Applied Sciences (Switzerland), 12 (3). http://eprints.utp.edu.my/28678/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
format Article
author Lo, M.
Vijaya Kumar, S.D.
Karuppanan, S.
Ovinis, M.
spellingShingle Lo, M.
Vijaya Kumar, S.D.
Karuppanan, S.
Ovinis, M.
An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect
author_facet Lo, M.
Vijaya Kumar, S.D.
Karuppanan, S.
Ovinis, M.
author_sort Lo, M.
title An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect
title_short An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect
title_full An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect
title_fullStr An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect
title_full_unstemmed An Artificial Neural Network-Based Equation for Predicting the Remaining Strength of Mid-to-High Strength Pipelines with a Single Corrosion Defect
title_sort artificial neural network-based equation for predicting the remaining strength of mid-to-high strength pipelines with a single corrosion defect
publisher MDPI
publishDate 2022
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124343364&doi=10.3390%2fapp12031722&partnerID=40&md5=5fda8310cdc5a3a41c9ffd55640ffb8e
http://eprints.utp.edu.my/28678/
_version_ 1738656873984294912
score 13.18916

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