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:
Two-view LSTM variational auto-encoder for fault detection and diagnosis in multivariable manufacturing processes
Qi Li, Yuwei Ren, Yixian Fang, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 29, pp. 22007-22026
Closed Access | Times Cited: 6
Qi Li, Yuwei Ren, Yixian Fang, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 29, pp. 22007-22026
Closed Access | Times Cited: 6
Showing 6 citing articles:
Small data challenges for intelligent prognostics and health management: a review
Chuanjiang Li, Shaobo Li, Yixiong Feng, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 23
Chuanjiang Li, Shaobo Li, Yixiong Feng, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 23
Hybrid physics-infused 1D-CNN based deep learning framework for diesel engine fault diagnostics
Shubhendu Kumar Singh, Raj Pradip Khawale, Subhashis Hazarika, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 28, pp. 17511-17539
Closed Access | Times Cited: 4
Shubhendu Kumar Singh, Raj Pradip Khawale, Subhashis Hazarika, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 28, pp. 17511-17539
Closed Access | Times Cited: 4
Multi-fault diagnosis and fault degree identification in hydraulic systems based on fully convolutional networks and deep feature fusion
Peng Zhang, Wenkai Hu, Weihua Cao, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 16, pp. 9125-9140
Closed Access | Times Cited: 2
Peng Zhang, Wenkai Hu, Weihua Cao, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 16, pp. 9125-9140
Closed Access | Times Cited: 2
Three‐layer deep learning network random trees for fault detection in chemical production process
Ming Lu, Zhen Gao, Ying Zou, et al.
The Canadian Journal of Chemical Engineering (2024)
Open Access | Times Cited: 1
Ming Lu, Zhen Gao, Ying Zou, et al.
The Canadian Journal of Chemical Engineering (2024)
Open Access | Times Cited: 1
Unsupervised Hybrid Models Integrating Deep Autoencoders and Process Controllers’ Models for Enhanced Process Monitoring and Fault Detection
Mohammad Aghaee, Stéphane Krau, Ibrahim Melih Tamer, et al.
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 33, pp. 14748-14760
Closed Access
Mohammad Aghaee, Stéphane Krau, Ibrahim Melih Tamer, et al.
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 33, pp. 14748-14760
Closed Access
Industrial Process Fault Detection Based on IGA‐Combinatorial Model Decision Mechanism
Shujuan Wei, Yongsheng Qi, Liqiang Liu, et al.
Journal of Chemometrics (2024)
Closed Access
Shujuan Wei, Yongsheng Qi, Liqiang Liu, et al.
Journal of Chemometrics (2024)
Closed Access
