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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:

Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network
Peng Jiang, Zhixin Hu, Jun Liu, et al.
Sensors (2016) Vol. 16, Iss. 10, pp. 1695-1695
Open Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

A novel deep learning based fault diagnosis approach for chemical process with extended deep belief network
Yalin Wang, Zhuofu Pan, Xiaofeng Yuan, et al.
ISA Transactions (2019) Vol. 96, pp. 457-467
Closed Access | Times Cited: 346
ReLTanh: An activation function with vanishing gradient resistance for SAE-based DNNs and its application to rotating machinery fault diagnosis
Xin Wang, Qin Yi, Yi Wang, et al.
Neurocomputing (2019) Vol. 363, pp. 88-98
Closed Access | Times Cited: 146
One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes
Shumei Chen, Jianbo Yu, Shijin Wang
Journal of Process Control (2020) Vol. 87, pp. 54-67
Closed Access | Times Cited: 142
Water quality prediction based on recurrent neural network and improved evidence theory: a case study of Qiantang River, China
Lei Li, Peng Jiang, Huan Xu, et al.
Environmental Science and Pollution Research (2019) Vol. 26, Iss. 19, pp. 19879-19896
Closed Access | Times Cited: 132
Deep Learning in Visual Computing and Signal Processing
Danfeng Xie, Lei Zhang, Bai Li
Applied Computational Intelligence and Soft Computing (2017) Vol. 2017, pp. 1-13
Open Access | Times Cited: 114
Cost sensitive active learning using bidirectional gated recurrent neural networks for imbalanced fault diagnosis
Peng Peng, Wenjia Zhang, Yi Zhang, et al.
Neurocomputing (2020) Vol. 407, pp. 232-245
Closed Access | Times Cited: 104
Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS
Moshen Kuai, Gang Cheng, Yusong Pang, et al.
Sensors (2018) Vol. 18, Iss. 3, pp. 782-782
Open Access | Times Cited: 84
Fault detection in Tennessee Eastman process with temporal deep learning models
Ildar Lomov, Mark Lyubimov, Ilya Makarov, et al.
Journal of Industrial Information Integration (2021) Vol. 23, pp. 100216-100216
Closed Access | Times Cited: 78
An Imbalance Modified Deep Neural Network With Dynamical Incremental Learning for Chemical Fault Diagnosis
Zhixin Hu, Peng Jiang
IEEE Transactions on Industrial Electronics (2018) Vol. 66, Iss. 1, pp. 540-550
Closed Access | Times Cited: 71
Fault detection and diagnosis with a novel source-aware autoencoder and deep residual neural network
Nima Amini, Qinqin Zhu
Neurocomputing (2021) Vol. 488, pp. 618-633
Closed Access | Times Cited: 48
A Novel Fault Diagnosis Approach for Chillers Based on 1-D Convolutional Neural Network and Gated Recurrent Unit
Zhuozheng Wang, Yingjie Dong, Wei Liu, et al.
Sensors (2020) Vol. 20, Iss. 9, pp. 2458-2458
Open Access | Times Cited: 48
Deep semi-supervised generative adversarial fault diagnostics of rolling element bearings
David Verstraete, Enrique López Droguett, Viviana Meruane, et al.
Structural Health Monitoring (2019) Vol. 19, Iss. 2, pp. 390-411
Closed Access | Times Cited: 44
Abnormality Monitoring in the Blast Furnace Ironmaking Process Based on Stacked Dynamic Target-Driven Denoising Autoencoders
Ke Jiang, Zhaohui Jiang, Yongfang Xie, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 3, pp. 1854-1863
Open Access | Times Cited: 39
One-dimensional convolutional neural network-based active feature extraction for fault detection and diagnosis of industrial processes and its understanding via visualization
Shumei Chen, Jianbo Yu, Shijin Wang
ISA Transactions (2021) Vol. 122, pp. 424-443
Closed Access | Times Cited: 35
An adaptive imbalance modified online broad learning system-based fault diagnosis for imbalanced chemical process data stream
Jinkun Men, C.M. Zhao
Expert Systems with Applications (2023) Vol. 234, pp. 121159-121159
Closed Access | Times Cited: 14
A classification-driven neuron-grouped SAE for feature representation and its application to fault classification in chemical processes
Zhuofu Pan, Yalin Wang, Xiaofeng Yuan, et al.
Knowledge-Based Systems (2021) Vol. 230, pp. 107350-107350
Closed Access | Times Cited: 28
Sparsity and manifold regularized convolutional auto-encoders-based feature learning for fault detection of multivariate processes
Chengyi Zhang, Jianbo Yu, Lyujiangnan Ye
Control Engineering Practice (2021) Vol. 111, pp. 104811-104811
Closed Access | Times Cited: 23
Layered and Real-Valued Negative Selection Algorithm for Fault Detection
Anam Abid, Muhammad Tahir Khan, Clarence W. de Silva
IEEE Systems Journal (2017) Vol. 12, Iss. 3, pp. 2960-2969
Closed Access | Times Cited: 31
Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS
Moshen Kuai, Gang Cheng, Yusong Pang, et al.
(2018)
Open Access | Times Cited: 30
A Novelty Detection Approach for Tendons of Prestressed Concrete Bridges Based on a Convolutional Autoencoder and Acceleration Data
Kanghyeok Lee, Seunghoo Jeong, Sung‐Han Sim, et al.
Sensors (2019) Vol. 19, Iss. 7, pp. 1633-1633
Open Access | Times Cited: 27
Deep-Learning-Based Remaining Useful Life Prediction Based on a Multi-Scale Dilated Convolution Network
Feiyue Deng, Yan Bi, Yongqiang Liu, et al.
Mathematics (2021) Vol. 9, Iss. 23, pp. 3035-3035
Open Access | Times Cited: 22
Hidden representations in deep neural networks: Part 1. Classification problems
Abhishek Sivaram, Laya Das, Venkat Venkatasubramanian
Computers & Chemical Engineering (2019) Vol. 134, pp. 106669-106669
Closed Access | Times Cited: 24
One-dimensional residual convolutional auto-encoder for fault detection in complex industrial processes
Jianbo Yu, Xing Liu
International Journal of Production Research (2021) Vol. 60, Iss. 18, pp. 5655-5674
Closed Access | Times Cited: 19
The Machine Learning Life Cycle in Chemical Operations – Status and Open Challenges
Marco Gärtler, Valentin Khaydarov, Benjamin Klöpper, et al.
Chemie Ingenieur Technik (2021) Vol. 93, Iss. 12, pp. 2063-2080
Closed Access | Times Cited: 19
Insights into enhanced machine learning techniques for surface water quantity and quality prediction based on data pre-processing algorithms
Javad Panahi, Reza Mastouri, Saeid Shabanlou
Journal of Hydroinformatics (2022) Vol. 24, Iss. 4, pp. 875-897
Open Access | Times Cited: 12
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