Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Greedy stochastic configuration networks for ill-posed problems
Tao Zhou, Yang Wang, Guanci Yang, et al.
Knowledge-Based Systems (2023) Vol. 269, pp. 110464-110464
Closed Access | Times Cited: 11

Showing 11 citing articles:

A multi-scale analysis method with multi-feature selection for house prices forecasting
Jin Shao, Lean Yu, Nengmin Zeng, et al.
Applied Soft Computing (2025), pp. 112779-112779
Closed Access | Times Cited: 2
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: 4
Intelligent fault diagnosis for unbalanced battery data using adversarial domain expansion and enhanced stochastic configuration networks
Sizhe Liu, XU De-zhi, Yujian Ye, et al.
Information Sciences (2024) Vol. 687, pp. 121399-121399
Closed Access | Times Cited: 3
2D convolutional stochastic configuration networks
Junqi Li, Dianhui Wang
Knowledge-Based Systems (2024) Vol. 300, pp. 112249-112249
Open Access | Times Cited: 3
Forecasting house price index with social media sentiment: A decomposition–ensemble approach
Jin Shao, Lean Yu, Jingke Hong, et al.
Journal of Forecasting (2024) Vol. 44, Iss. 1, pp. 216-241
Closed Access | Times Cited: 3
Greedy deep stochastic configuration networks ensemble with boosting negative correlation learning
Chenglong Zhang, Yang Wang, David Zhang
Information Sciences (2024) Vol. 680, pp. 121140-121140
Closed Access | Times Cited: 2
Self-organizing hierarchical incremental learning framework and universal approximation analysis based on stochastic configuration mechanism
Bao Shi, Yongsheng Ou, Degang Wang, et al.
Information Sciences (2024) Vol. 688, pp. 121402-121402
Closed Access | Times Cited: 2
Temporal online self-learning stochastic configuration networks: A study on strip deviation prediction
Han Gao, Yumei Qin, Hao Yuan, et al.
Information Sciences (2024), pp. 121446-121446
Closed Access
Multi-level Optimizing of Parameters in Stochastic Configuration Networks based on Cloud Model and Nutcracker Optimization Algorithm
Ying Han, Yuanhao Yu, Hao Wu, et al.
Information Sciences (2024), pp. 121495-121495
Closed Access
Adaptive inertia weights: an effective way to improve parameter estimation of hidden layer in stochastic configuration networks
Ying Han, Yuanhao Yu, Kun Li
International Journal of Machine Learning and Cybernetics (2024)
Closed Access
GA-DE: an integrated meta-heuristic approach for optimizing feedforward neural networks
Mengying Shang, Mengnan Tian, X.X. Wang
The Journal of Supercomputing (2024) Vol. 81, Iss. 1
Closed Access
Page 1

Scroll to top