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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:

Optimizing Deep Belief Echo State Network with a Sensitivity Analysis Input Scaling Auto-Encoder algorithm
Heshan Wang, Q. M. Jonathan Wu, Jianbin Xin, et al.
Knowledge-Based Systems (2019) Vol. 191, pp. 105257-105257
Closed Access | Times Cited: 13

Showing 13 citing articles:

DAFA-BiLSTM: Deep Autoregression Feature Augmented Bidirectional LSTM network for time series prediction
Heshan Wang, Yiping Zhang, Jing Liang, et al.
Neural Networks (2022) Vol. 157, pp. 240-256
Closed Access | Times Cited: 60
MBSSA-Bi-AESN: Classification prediction of bi-directional adaptive echo state network based on modified binary salp swarm algorithm and feature selection
Xunjin Wu, Jianming Zhan, Tianrui Li, et al.
Applied Intelligence (2024) Vol. 54, Iss. 2, pp. 1706-1733
Closed Access | Times Cited: 8
A Systematic Review of Echo State Networks From Design to Application
Chenxi Sun, Moxian Song, Derun Cai, et al.
IEEE Transactions on Artificial Intelligence (2022) Vol. 5, Iss. 1, pp. 23-37
Closed Access | Times Cited: 35
A Review of Designs and Applications of Echo State Networks
Chenxi Sun, Moxian Song, Shenda Hong, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 40
Echo state network with logistic mapping and bias dropout for time series prediction
Heshan Wang, Yu-xi Liu, Peng Lu, et al.
Neurocomputing (2022) Vol. 489, pp. 196-210
Closed Access | Times Cited: 21
Data-driven reduced-order modeling for nonlinear aerodynamics using an autoencoder neural network
Abhijith Moni, Weigang Yao, Hossein Malekmohamadi
Physics of Fluids (2024) Vol. 36, Iss. 1
Closed Access | Times Cited: 4
Growing deep echo state network with supervised learning for time series prediction
Ying Li, Fanjun Li
Applied Soft Computing (2022) Vol. 128, pp. 109454-109454
Closed Access | Times Cited: 12
Rotating machinery faults detection method based on deep echo state network
Xin Li, Fengrong Bi, Lipeng Zhang, et al.
Applied Soft Computing (2022) Vol. 127, pp. 109335-109335
Closed Access | Times Cited: 9
Deep belief improved bidirectional LSTM for multivariate time series forecasting
Keruo Jiang, Zhen Huang, Xinyan Zhou, et al.
Mathematical Biosciences & Engineering (2023) Vol. 20, Iss. 9, pp. 16596-16627
Open Access | Times Cited: 5
Feature Recognition of English Based on Deep Belief Neural Network and Big Data Analysis
Xiaoling Liu
Computational Intelligence and Neuroscience (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 9
An Inkjet-Printed Flexible Memristor Device for Echo State Networks
Tasnim Zaman Adry, Shahrin Akter, Sazia A. Eliza, et al.
(2024), pp. 740-744
Closed Access
Predicting solutions of the stochastic fractional order dynamical system using machine learning
Zifei Lin, Jia-Li Zhao, Yan-Ming Liang, et al.
Theoretical and Applied Mechanics Letters (2023) Vol. 13, Iss. 3, pp. 100433-100433
Open Access | Times Cited: 1
A Weight Optimization Method of Deep Echo State Network Based on Improved Knowledge Evolution
Yuanhui Wang, Jian Zhou, Hui Cai, et al.
2021 China Automation Congress (CAC) (2022), pp. 395-400
Closed Access
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