Closure to “Predicting Solid-Particle Erosion Rate of Pipelines Using Support Vector Machine with Improved Sparrow Search Algorithm”-Reference-Cited by-同舟云学术

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Closure to “Predicting Solid-Particle Erosion Rate of Pipelines Using Support Vector Machine with Improved Sparrow Search Algorithm”

Published:2024-05 Issue:2 Volume:15 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Peng Haoyan¹,Lu Hongfang²,Xu Zhao-Dong³

Affiliation:

1. Ph.D. Candidate, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China.

2. Associate Professor, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China.

3. Director and Professor, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JPSEA2.PSENG-1612

Reference1 articles.

1. Carbon sink price prediction based on radial basis kernel function support vector machine regression model

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