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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 high-precision and transparent step-wise diagnostic framework for hot-rolled strip crown
Chengyan Ding, Jie Sun, Xiaojian Li, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 144-157
Closed Access | Times Cited: 16

Showing 16 citing articles:

IoT-based framework for digital twins in steel production: A case study of key parameter prediction and optimization for CSR
Jingdong Li, Xiaochen Wang, Quan Yang, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123909-123909
Closed Access | Times Cited: 8
基于混合多阶集成模型的非平衡热轧带钢凸度智能诊断
Chengyan Ding, Jie Sun, Xiaojian Li, et al.
Journal of Central South University (2024) Vol. 31, Iss. 3, pp. 762-782
Closed Access | Times Cited: 5
Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling
Jie Sun, Chen Shang, Chengyan Ding, et al.
Digital Twin (2025) Vol. 4, pp. 10-10
Open Access
Explainable machine learning for predicting mechanical properties of hot-rolled steel pipe
Jingdong Li, Youzhao Sun, Xiaochen Wang, et al.
Journal of Iron and Steel Research International (2025)
Closed Access
Novel shape control system of hot-rolled strip based on machine learning fused mechanism model
LingMing Meng, Jingguo Ding, Xiaojian Li, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124789-124789
Closed Access | Times Cited: 3
Modeling and Simulation of Shape Control Based on Digital Twin Technology in Hot Strip Rolling
Youzhao Sun, Jingdong Li, Yamin Sun, et al.
Sensors (2024) Vol. 24, Iss. 2, pp. 614-614
Open Access | Times Cited: 2
A novel deep ensemble reinforcement learning based control method for strip flatness in cold rolling steel industry
Wen Peng, Jiawei Lei, Chengyan Ding, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108695-108695
Closed Access | Times Cited: 2
An interpretable framework for high-precision flatness prediction in strip cold rolling
Chengyan Ding, Jun-Cheng Ye, Jia-Wei Lei, et al.
Journal of Materials Processing Technology (2024) Vol. 329, pp. 118452-118452
Closed Access | Times Cited: 2
Industrial Big Data‐Driven Modeling and Prediction for Hot‐Rolled Strip Crown with Multigrade and Multispecification Data
Dewei Xu, Chengyan Ding, Yu Liu, et al.
steel research international (2024) Vol. 95, Iss. 7
Closed Access | Times Cited: 1
Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling
Jie Sun, Chen Shang, Chengyan Ding, et al.
Digital Twin (2024) Vol. 4, pp. 10-10
Open Access | Times Cited: 1
Prediction and Analysis of Hot Rolling Strip Tension Based on Back Propagation Neural Network
Hao Yuan, Yiwei Ma, Xu Li, et al.
Research Square (Research Square) (2024)
Open Access
A Novel Model Based on PSO-GA-RBF Approach for Predicting Roll Gap During Unsteady Processes
Ruixiao Zhang, Chaoxing Mao, Jinkai Hu, et al.
(2024), pp. 636-641
Closed Access
A novel cost-sensitive quality determination framework in hot rolling steel industry
Chengyan Ding, Jun-Cheng Ye, L Wang, et al.
Information Sciences (2024) Vol. 678, pp. 121054-121054
Closed Access
An Improved VAE-Based Quality Prediction Method with Application to a Hot Strip Rolling Mill Process
Yundan Liu, Kai Zhang, Xiaowen Zhang
2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS) (2024), pp. 783-788
Closed Access
Multi-dimension and multi-modal rolling mill vibration prediction model based on multi-level network fusion
Shu-zong Chen, Yunxiao Liu, Yunlong Wang, et al.
Journal of Central South University (2024)
Closed Access
Application of novel interpretable machine learning framework for strip flatness prediction during tandem cold rolling
Jingdong Li, Youzhao Sun, Xiaochen Wang, et al.
Measurement (2024), pp. 116516-116516
Closed Access
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