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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:

Ensemble deep relevant learning framework for semi-supervised soft sensor modeling of industrial processes
Jean Mário Moreira de Lima, Fábio Meneghetti Ugulino de Araújo
Neurocomputing (2021) Vol. 462, pp. 154-168
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Latent variable models in the era of industrial big data: Extension and beyond
Xiangyin Kong, Xiaoyu Jiang, Bingxin Zhang, et al.
Annual Reviews in Control (2022) Vol. 54, pp. 167-199
Open Access | Times Cited: 63
An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process
Lei Hua, Chu Zhang, Wei Sun, et al.
ISA Transactions (2022) Vol. 136, pp. 139-151
Closed Access | Times Cited: 44
Semi-supervised ensemble support vector regression based soft sensor for key quality variable estimation of nonlinear industrial processes with limited labeled data
Zheng Li, Huaiping Jin, Shoulong Dong, et al.
Process Safety and Environmental Protection (2022) Vol. 179, pp. 510-526
Closed Access | Times Cited: 32
Online quality estimation in chemical processes with random subspace deep partial least squares model
Ouguan Xu, Zeyu Yang, Zhiqiang Ge
Chemical Engineering Science (2025), pp. 121295-121295
Closed Access
Novel dynamic data-driven modeling based on feature enhancement with derivative memory LSTM for complex industrial process
Xiuli Zhu, Jiajun Xu, Zixuan Fu, et al.
Neurocomputing (2025), pp. 129619-129619
Closed Access
Novel Deep Layers-Extended Autoencoder With Correlation and Its Industrial Soft Sensing
Ye Tian, Qun‐Xiong Zhu, Yan‐Lin He
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 1, pp. 596-604
Closed Access | Times Cited: 13
A novel reinforced incomplete cyber-physics ensemble with error compensation learning for within-batch quality prediction
Yi Shan Lee, Junghui Chen
Advanced Engineering Informatics (2025) Vol. 65, pp. 103172-103172
Closed Access
Novel CNN-based transformer integrating Boruta algorithm for production prediction modeling and energy saving of industrial processes
Yongming Han, Longkun Han, Xinwei Shi, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124447-124447
Closed Access | Times Cited: 3
Soft Sensors Using Heterogeneous Image Features for Moisture Detection of Sintering Mixture in the Sintering Process
Zhaohui Jiang, Jicheng Zhu, Dong Pan, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 8
A novel semi-supervised soft sensor modeling method based on deep dynamic and semantic information extraction for concentrate grade prediction in froth flotation
Boyi Zheng, Degang Xu, Guanzheng Tan, et al.
Minerals Engineering (2023) Vol. 201, pp. 108179-108179
Closed Access | Times Cited: 8
A semi-supervised feature contrast convolutional neural network for processes fault diagnosis
Yuguo Yang, Hongbo Shi, Yang Tao, et al.
Journal of the Taiwan Institute of Chemical Engineers (2023) Vol. 151, pp. 105098-105098
Closed Access | Times Cited: 8
Adversarial Training-Based Deep Layer-Wise Probabilistic Network for Enhancing Soft Sensor Modeling of Industrial Processes
Yongfang Xie, Jie Wang, Shiwen Xie, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2023) Vol. 54, Iss. 2, pp. 972-984
Closed Access | Times Cited: 8
A denoising semi-supervised deep learning model for remaining useful life prediction of turbofan engine degradation
Youming Wang, Yue Wang
Applied Intelligence (2023) Vol. 53, Iss. 19, pp. 22682-22699
Closed Access | Times Cited: 7
Adversarial Attacks for Neural Network-Based Industrial Soft Sensors: Mirror Output Attack and Translation Mirror Output Attack
Lei Chen, Qunxiong Zhu, Yan‐Lin He
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 2, pp. 2378-2386
Closed Access | Times Cited: 7
Memory-Adaptive Supervised LSTM Networks for Deep Soft Sensor Development of Industrial Processes
Feifan Shen, Jiayang Wu, Lingjian Ye, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 13, pp. 21641-21654
Closed Access | Times Cited: 2
Deep Learning–Based Soft Sensors for Improving the Flexibility for Automation of Industry
Rami Ayadi, Rasha M. Abd El-Aziz, Ahmed I. Taloba, et al.
Wireless Communications and Mobile Computing (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 9
A Soft Sensor Model for Predicting the Flow of a Hydraulic Pump Based on Graph Convolutional Network–Long Short-Term Memory
Shengfei Ji, Wei Li, Yong Wang, et al.
Actuators (2024) Vol. 13, Iss. 1, pp. 38-38
Open Access | Times Cited: 1
Pseudo-Labeling Optimization Based Ensemble Semi-Supervised Soft Sensor in the Process Industry
Youwei Li, Huaiping Jin, Shoulong Dong, et al.
Sensors (2021) Vol. 21, Iss. 24, pp. 8471-8471
Open Access | Times Cited: 6
A Multi-Rate Probabilistic Slow Feature Regression Model for Dynamic Feature Learning and Industrial Soft Sensor Development
Miao Zhang, Zhiwei Wen, Le Zhou
IEEE Access (2022) Vol. 10, pp. 128994-129003
Open Access | Times Cited: 4
A Novel Prediction Method for Blast Furnace Gas Utilization Rate Based on Dynamic Weighted Stacked Output‐Relevant Autoencoder
Zhaohui Jiang, Jicheng Zhu, Dong Pan, et al.
steel research international (2022) Vol. 94, Iss. 5
Open Access | Times Cited: 3
Accurate External Angular Rate Sensing Method for Gyrowheel Using a Hybrid Dual-Module Model
Yuyu Zhao, Yi Tian, Yuxiao Wang, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 7, pp. 10296-10306
Closed Access
A Novel Label-Aware Global Graph Construction Method and Spiking-Coded Graph Neural Network for Intelligent Process Fault Diagnosis
Dazi Li, Yurui Zhu, Zhihuan Song, et al.
Neurocomputing (2024), pp. 128707-128707
Closed Access
A novel self-training framework for semi-supervised soft sensor modeling based on indeterminate variational autoencoder
Hengqian Wang, Lei Chen, Kuangrong Hao, et al.
Information Sciences (2024), pp. 121565-121565
Closed Access
A Local Semisupervised Soft Sensor Modeling Method Based on SAE Neural Networks for Spatiotemporal Dynamic Chemical Process
Shuang Wang, Longhao Li, Housheng Zhang, et al.
Industrial & Engineering Chemistry Research (2024)
Closed Access
A framework for enhancing industrial soft sensor learning models
João Guilherme Mattos, Patrick Nigri Happ, William Paulo Ducca Fernandes, et al.
Digital Chemical Engineering (2023) Vol. 8, pp. 100112-100112
Open Access | Times Cited: 1
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