Closure to “Predicting Solid-Particle Erosion Rate of Pipelines Using Support Vector Machine with Improved Sparrow Search Algorithm”
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VIEW THE ORIGINAL ARTICLEAuthors: Haoyan Peng, S.M.ASCE [email protected], Hongfang Lu, M.ASCE [email protected], and Zhao-Dong Xu, A.M.ASCE [email protected]Author Affiliations
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 15, Issue 2
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References
Yang, X., J. L. Mi, J. Jiang, J. W. Li, Q. S. Zhang, and M. M. Geng. 2022. “Carbon sink price prediction based on radial basis kernel function support vector machine regression model.” Int. J. Low Carbon Technol. 17 (Aug): 1075–1084. https://doi.org/10.1093/ijlct/ctac088.
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Journal of Pipeline Systems Engineering and Practice
Volume 15 • Issue 2 • May 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Oct 26, 2023
Accepted: Nov 20, 2023
Published online: Feb 7, 2024
Published in print: May 1, 2024
Discussion open until: Jul 7, 2024
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Ph.D. Candidate, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China. Email: [email protected]
Associate Professor, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China. Email: [email protected]
Director and Professor, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China (corresponding author). Email: [email protected]
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