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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A KPCA-BRANN based data-driven approach to model corrosion degradation of subsea oil pipelines
Xinhong Li, Ruichao Jia, Renren Zhang, et al.
Reliability Engineering & System Safety (2021) Vol. 219, pp. 108231-108231
Open Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

Advances in corrosion growth modeling for oil and gas pipelines: A review
Haonan Ma, Weidong Zhang, Yao Wang, et al.
Process Safety and Environmental Protection (2022) Vol. 171, pp. 71-86
Closed Access | Times Cited: 70
Evolution of corrosion prediction models for oil and gas pipelines: From empirical-driven to data-driven
Qinying Wang, Yuhui Song, Xingshou Zhang, et al.
Engineering Failure Analysis (2023) Vol. 146, pp. 107097-107097
Closed Access | Times Cited: 65
A critical review of machine learning algorithms in maritime, offshore, and oil & gas corrosion research: A comprehensive analysis of ANN and RF models
Md Mahadi Hasan Imran, Shahrizan Jamaludin, Ahmad Faisal Mohamad Ayob
Ocean Engineering (2024) Vol. 295, pp. 116796-116796
Closed Access | Times Cited: 20
Development of a CNN-based integrated surrogate model in evaluating the damage of buried pipeline under impact loads, considering the soil spatial variability
Fengyuan Jiang, Sheng Dong
Reliability Engineering & System Safety (2025), pp. 110801-110801
Closed Access | Times Cited: 2
The research progress and prospect of data mining methods on corrosion prediction of oil and gas pipelines
Lei Xu, Yunfu Wang, Lin Mo, et al.
Engineering Failure Analysis (2022) Vol. 144, pp. 106951-106951
Closed Access | Times Cited: 52
Residual strength prediction of corroded pipelines using multilayer perceptron and modified feedforward neural network
Zhanfeng Chen, Xuyao Li, Wen Wang, et al.
Reliability Engineering & System Safety (2022) Vol. 231, pp. 108980-108980
Closed Access | Times Cited: 48
Edge-cloud cooperation-driven smart and sustainable production for energy-intensive manufacturing industries
Shuaiyin Ma, Yuming Huang, Yang Liu, et al.
Applied Energy (2023) Vol. 337, pp. 120843-120843
Open Access | Times Cited: 41
A data-driven prediction model for maximum pitting corrosion depth of subsea oil pipelines using SSA-LSTM approach
Xinhong Li, Mengmeng Guo, Renren Zhang, et al.
Ocean Engineering (2022) Vol. 261, pp. 112062-112062
Closed Access | Times Cited: 40
Leakage diagnosis and localization of the gas extraction pipeline based on SA-PSO BP neural network
Jie Zhou, Haifei Lin, Shugang Li, et al.
Reliability Engineering & System Safety (2022) Vol. 232, pp. 109051-109051
Closed Access | Times Cited: 40
A machine learning methodology for probabilistic risk assessment of process operations: A case of subsea gas pipeline leak accidents
Xinhong Li, Jingwen Wang, Guoming Chen
Process Safety and Environmental Protection (2022) Vol. 165, pp. 959-968
Closed Access | Times Cited: 39
A novel neural network-based framework to estimate oil and gas pipelines life with missing input parameters
Nagoor Basha Shaik, Kittiphong Jongkittinarukorn, Watit Benjapolakul, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 15
Prediction of external corrosion rate for buried oil and gas pipelines: a novel deep learning with DNN and attention mechanism method
Yu Guang, Wenhe Wang, Hongwei Song, et al.
International Journal of Pressure Vessels and Piping (2024) Vol. 209, pp. 105218-105218
Closed Access | Times Cited: 14
Reliability analysis of corroded pipes using MFL signals and Residual Neural Networks
Yinuo Chen, Zhigang Tian, Haotian Wei, et al.
Process Safety and Environmental Protection (2024) Vol. 184, pp. 1131-1142
Closed Access | Times Cited: 11
Corrosion leakage risk diagnosis of oil and gas pipelines based on semi-supervised domain generalization model
Xingyuan Miao, Hong Zhao, Boxuan Gao, et al.
Reliability Engineering & System Safety (2023) Vol. 238, pp. 109486-109486
Closed Access | Times Cited: 21
Prediction of gas explosion pressures: A machine learning algorithm based on KPCA and an optimized LSSVM
Kai Zhang, Ke Zhang, Rui Bao
Journal of Loss Prevention in the Process Industries (2023) Vol. 83, pp. 105082-105082
Closed Access | Times Cited: 20
Interpretable machine learning for maximum corrosion depth and influence factor analysis
Yuhui Song, Qinying Wang, Xingshou Zhang, et al.
npj Materials Degradation (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 19
Probabilistic-based burst failure mechanism analysis and risk assessment of pipelines with random non-uniform corrosion defects, considering the interacting effects
Fengyuan Jiang, Sheng Dong
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109783-109783
Closed Access | Times Cited: 18
A data-driven methodology for predicting residual strength of subsea pipeline with double corrosion defects
Xinhong Li, Ruichao Jia, Renren Zhang
Ocean Engineering (2023) Vol. 279, pp. 114530-114530
Closed Access | Times Cited: 16
An optimized back propagation neural network on small samples spectral data to predict nitrite in water
Cailing Wang, Guohao Zhang, J. Yan
Environmental Research (2024) Vol. 247, pp. 118199-118199
Closed Access | Times Cited: 7
Prediction of the internal corrosion rate for oil and gas pipelines and influence factor analysis with interpretable ensemble learning
Jinlong Hu
International Journal of Pressure Vessels and Piping (2024), pp. 105329-105329
Closed Access | Times Cited: 6
An optimized decomposition integration model for deterministic and probabilistic air pollutant concentration prediction considering influencing factors
Fan Yang, Guangqiu Huang
Atmospheric Pollution Research (2024) Vol. 15, Iss. 7, pp. 102144-102144
Closed Access | Times Cited: 5
Prediction of internal corrosion rate for gas pipeline: a new method based on Transformer architecture
Li Tan, Yang Yang, Kemeng Zhang, et al.
Computers & Chemical Engineering (2025), pp. 109084-109084
Closed Access
Corroded submarine pipeline degradation prediction based on theory-guided IMOSOA-EL model
Xingyuan Miao, Hong Zhao
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109902-109902
Closed Access | Times Cited: 11
Emergency risk analysis of subsea capping stack in blowout scenario integrating numerical simulation with ANN model
Jingyu Zhu, Guoming Chen, Shaoyu Zhang
Ocean Engineering (2024) Vol. 296, pp. 116727-116727
Closed Access | Times Cited: 4
Distributed incipient fault detection with causality-based multi-perspective subblock partitioning for large-scale nonlinear processes
Ming Yin, Wei‐Hua Wang, Jiayi Tian, et al.
Process Safety and Environmental Protection (2024) Vol. 185, pp. 492-510
Closed Access | Times Cited: 4
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