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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:

Evaluation of machine learning methods for lithology classification using geophysical data
Thiago Santi Bressan, Marcelo Kehl de Souza, Tiago Jonatan Girelli, et al.
Computers & Geosciences (2020) Vol. 139, pp. 104475-104475
Closed Access | Times Cited: 183

Showing 26-50 of 183 citing articles:

Performance evaluation of machine learning-based classification with rock-physics analysis of geological lithofacies in Tarakan Basin, Indonesia
Gian Antariksa, Radhi Muammar, Jihwan Lee
Journal of Petroleum Science and Engineering (2021) Vol. 208, pp. 109250-109250
Closed Access | Times Cited: 44
Lithofacies classification and sequence stratigraphic description as a guide for the prediction and distribution of carbonate reservoir quality: A case study of the Upper Cretaceous Khasib Formation (East Baghdad oilfield, central Iraq)
Mohamed Abdel Fattah, Adnan Q. Mahdi, Mustafa A. Theyab, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 209, pp. 109835-109835
Closed Access | Times Cited: 42
Rock type classification based on petrophysical, geochemical, and core imaging data using machine and deep learning techniques
Negin Houshmand, Sebastian D. Goodfellow, Kamran Esmaeili, et al.
Applied Computing and Geosciences (2022) Vol. 16, pp. 100104-100104
Open Access | Times Cited: 34
Implementation of free and open-source semi-automatic feature engineering tool in landslide susceptibility mapping using the machine-learning algorithms RF, SVM, and XGBoost
Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2022) Vol. 37, Iss. 3, pp. 1067-1092
Closed Access | Times Cited: 29
Lithological Classification by Hyperspectral Images Based on a Two-Layer XGBoost Model, Combined with a Greedy Algorithm
Nan Lin, Jiawei Fu, Ranzhe Jiang, et al.
Remote Sensing (2023) Vol. 15, Iss. 15, pp. 3764-3764
Open Access | Times Cited: 19
Machine learning approaches for formation matrix volume prediction from well logs: Insights and lessons learned
Pamidi Venkata Durga Kannaiah, Neetish Kumar Maurya
Geoenergy Science and Engineering (2023) Vol. 229, pp. 212086-212086
Closed Access | Times Cited: 17
Knowledge-based machine learning for mineral classification in a complex tectonic regime of Yingxiu-Beichuan fault zone, Sichuan basin
Jar Ullah, Huan Li, Umar Ashraf, et al.
Geoenergy Science and Engineering (2023) Vol. 229, pp. 212077-212077
Closed Access | Times Cited: 16
Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary
Musaab A. A. Mohammed, Norbert Péter Szabó, Péter Szűcs
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 3, pp. 3693-3709
Open Access | Times Cited: 7
Improving the prediction performance of leaf water content by coupling multi-source data with machine learning in rice (Oryza sativa L.)
Xuenan Zhang, Haocong Xu, Yehong She, et al.
Plant Methods (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 7
Sudden cardiac death prediction based on the complete ensemble empirical mode decomposition method and a machine learning strategy by using ECG signals
Manuel A. Centeno-Bautista, Andrea V. Perez-Sanchez, Juan P. Amézquita-Sánchez, et al.
Measurement (2024) Vol. 236, pp. 115052-115052
Closed Access | Times Cited: 7
Geo-constrained clustering of resistivity data revealing the heterogeneous lithological architectures and the distinctive geoelectrical signature of shallow deposits
Paolo Ciampi, Leonardo Maria Giannini, Giorgio Cassiani, et al.
Engineering Geology (2024) Vol. 337, pp. 107589-107589
Open Access | Times Cited: 7
K-Means Featurizer: A booster for intricate datasets
Kouao Laurent Kouadio, Jianxin Liu, Rong Liu, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1203-1228
Closed Access | Times Cited: 6
Integrating machine learning and data analytics for geostatistical characterization of clastic reservoirs
Watheq J. Al‐Mudhafar
Journal of Petroleum Science and Engineering (2020) Vol. 195, pp. 107837-107837
Closed Access | Times Cited: 48
Lithofacies identification in carbonate reservoirs by multiple kernel Fisher discriminant analysis using conventional well logs: A case study in A oilfield, Zagros Basin, Iraq
Shaoqun Dong, Lianbo Zeng, Xiangyi Du, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 210, pp. 110081-110081
Closed Access | Times Cited: 39
Three-dimensional geotechnical-layer mapping in Seoul using borehole database and deep neural network-based model
Hansaem Kim, Yoonsoo Ji
Engineering Geology (2021) Vol. 297, pp. 106489-106489
Closed Access | Times Cited: 37
Improving water status prediction of winter wheat using multi-source data with machine learning
Bo Shi, Yifan Yuan, Tingxuan Zhuang, et al.
European Journal of Agronomy (2022) Vol. 139, pp. 126548-126548
Closed Access | Times Cited: 25
How to improve machine learning models for lithofacies identification by practical and novel ensemble strategy and principles
Shaoqun Dong, Yan-Ming Sun, Tao Xu, et al.
Petroleum Science (2022) Vol. 20, Iss. 2, pp. 733-752
Open Access | Times Cited: 25
Intelligent Classification of Surrounding Rock of Tunnel Based on 10 Machine Learning Algorithms
Siguang Zhao, Mingnian Wang, Wenhao Yi, et al.
Applied Sciences (2022) Vol. 12, Iss. 5, pp. 2656-2656
Open Access | Times Cited: 23
A Two-Stage Attention-Based Hierarchical Transformer for Turbofan Engine Remaining Useful Life Prediction
Zhengyang Fan, Wanru Li, Kuo‐Chu Chang
Sensors (2024) Vol. 24, Iss. 3, pp. 824-824
Open Access | Times Cited: 5
A Review on Intelligent Recognition with Logging Data: Tasks, Current Status and Challenges
Xinyi Zhu, Hongbing Zhang, Quan Ren, et al.
Surveys in Geophysics (2024) Vol. 45, Iss. 5, pp. 1493-1526
Closed Access | Times Cited: 5
Pattern Classification
Katherine L. Silversides
Encyclopedia of earth sciences series/Encyclopedia of earth sciences (2021), pp. 1-3
Closed Access | Times Cited: 32
Evaluation of machine learning methods for rock mass classification
Allan Erlikhman Medeiros Santos, Milene Sabino Lana, Tiago Martins Pereira
Neural Computing and Applications (2021) Vol. 34, Iss. 6, pp. 4633-4642
Closed Access | Times Cited: 27
Multi-scale spatiotemporal feature lithology identification method based on split-frequency weighted reconstruction
Zongren Wang, Kai Xie, Chang Wen, et al.
Geoenergy Science and Engineering (2023) Vol. 226, pp. 211794-211794
Closed Access | Times Cited: 11
Accuracy assessment of various supervised machine learning algorithms in litho-facies classification from seismic data in the Penobscot field, Scotian Basin
Satya Narayan, Suresh Konka, Akash Chandra, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 11
Residual Convolutional Neural Network for Lithology Classification: A Case Study of an Iranian Gas Field
S. H. Mousavi, Seyed Mojtaba Hosseini‐Nasab
International Journal of Energy Research (2024) Vol. 2024, pp. 1-25
Open Access | Times Cited: 4

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