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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 19, 2023 - Issue 8
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Articles

On the influence of input data uncertainty on sewer deterioration models – a case study in Norway

Thomas Fugledalena Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway;b Department of Water Engineering, Sweco Norge AS, Oslo, Norway
,
Marius Møller Rokstada Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, NorwayORCID Iconhttps://orcid.org/0000-0003-4650-3554
ORCID Icon &
Franz Tscheikner-Gratla Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, NorwayCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-2545-6683
ORCID Icon
Pages 1064-1075 | Received 06 Apr 2021, Accepted 12 Sep 2021, Published online: 03 Nov 2021

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L. V. Nguyen & S. Razak. (2023) Predicting sewer structural condition using hybrid machine learning algorithms. Urban Water Journal 20:7, pages 882-896.
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Articles from other publishers (1)

Jorge Fernando Marquez-Peñaranda, Mauricio Sanchez-Silva & Emilio Bastidas-Arteaga. (2022) Probabilistic Assessment of Biodeterioration Effects on Reinforced Concrete Sewers. Corrosion and Materials Degradation 3:3, pages 333-348.
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