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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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/ |
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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 |
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2022 |
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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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1738656873984294912 |
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13.18916 |