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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:

A data-driven workflow based on multisource transfer machine learning for gas-bearing probability distribution prediction: A case study
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Geophysics (2023) Vol. 88, Iss. 4, pp. B163-B177
Closed Access | Times Cited: 9

Showing 9 citing articles:

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Petroleum Science (2024) Vol. 21, Iss. 4, pp. 2329-2344
Open Access | Times Cited: 3
Transfer learning-based hybrid deep learning method for gas-bearing distribution prediction with insufficient training samples and uncertainty analysis
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Energy (2024) Vol. 299, pp. 131414-131414
Closed Access | Times Cited: 2
Tracer Research Methods for Hydrocarbon Substances in Shale Oil Reservoirs
Manfei Chen, Wenhao Tang, Li Wang, et al.
Chemistry and Technology of Fuels and Oils (2024) Vol. 60, Iss. 1, pp. 197-206
Closed Access | Times Cited: 1
A Framework for Predicting the Gas-Bearing Distribution of Unconventional Reservoirs by Deep Learning
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Natural Resources Research (2024) Vol. 33, Iss. 4, pp. 1625-1655
Closed Access | Times Cited: 1
A Parametric Study of MPSO-ANN Techniques in Gas-Bearing Distribution Prediction Using Multicomponent Seismic Data
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Remote Sensing (2023) Vol. 15, Iss. 16, pp. 3987-3987
Open Access | Times Cited: 2
An improved integration strategy for prediction of shear wave velocity using petrophysical logs: Integration of spatiotemporal and small sample nonlinear feature
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
Geoenergy Science and Engineering (2023) Vol. 230, pp. 212270-212270
Closed Access | Times Cited: 2
A hybrid model based on unsupervised learning for seismic response feature extraction and gas-bearing reservoir prediction using longitudinal and transverse waves seismic data in low-degree exploration areas: A case study
Kai Zhang, Niantian Lin, Jiuqiang Yang, et al.
Journal of Applied Geophysics (2024) Vol. 225, pp. 105382-105382
Closed Access
Method and application of sand body thickness prediction based on virtual sample machine learning
Yan Zhen, Zhen Zhao, Xiaoming Zhao, et al.
Geophysics (2024) Vol. 89, Iss. 6, pp. M169-M184
Closed Access
Gas-Bearing Prediction Using a Hybrid Method Based on a Combination of PCA-FastICA and CNN With the Attention Mechanism
Jiuqiang Yang, Niantian Lin, Kai Zhang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2023) Vol. 61, pp. 1-18
Closed Access | Times Cited: 1
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