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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 Hybrid Logistic Regression: Gene Expression Programming Model and Its Application to Mineral Prospectivity Mapping
Fan Xiao, Weilin Chen, Jun Wang, et al.
Natural Resources Research (2021) Vol. 31, Iss. 4, pp. 2041-2064
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Stacking: A novel data-driven ensemble machine learning strategy for prediction and mapping of Pb-Zn prospectivity in Varcheh district, west Iran
Mahsa Hajihosseinlou, Abbas Maghsoudi, Reza Ghezelbash
Expert Systems with Applications (2023) Vol. 237, pp. 121668-121668
Closed Access | Times Cited: 56
Simulation-based mineral prospectivity modeling and Gray Wolf optimization algorithm for delimiting exploration targets
Kamran Mostafaei, Mahyar Yousefi, Oliver P. Kreuzer, et al.
Ore Geology Reviews (2025), pp. 106458-106458
Open Access | Times Cited: 3
Enhancing the exploitation of natural resources for green energy: An application of LSTM-based meta-model for aluminum prices forecasting
Moses Olabhele Esangbedo, Blessing Olamide Taiwo, Hawraa H. Abbas, et al.
Resources Policy (2024) Vol. 92, pp. 105014-105014
Closed Access | Times Cited: 12
Mineral Prospectivity Mapping Using Deep Self-Attention Model
Bojun Yin, Renguang Zuo, Siquan Sun
Natural Resources Research (2022) Vol. 32, Iss. 1, pp. 37-56
Closed Access | Times Cited: 34
Developments in Quantitative Assessment and Modeling of Mineral Resource Potential: An Overview
Yue Liu, Emmanuel John M. Carranza, Qinglin Xia
Natural Resources Research (2022) Vol. 31, Iss. 4, pp. 1825-1840
Open Access | Times Cited: 30
Combination of Machine Learning Algorithms with Concentration-Area Fractal Method for Soil Geochemical Anomaly Detection in Sediment-Hosted Irankuh Pb-Zn Deposit, Central Iran
Sasan Farhadi, Peyman Afzal, Mina Boveiri Konari, et al.
Minerals (2022) Vol. 12, Iss. 6, pp. 689-689
Open Access | Times Cited: 28
The world-class carbonate-hosted Fankou Zn-Pb deposit in China. Part III. Critical metal Ga is enriched in late stage and low temperature sphalerite
Yihan Wu, Yi Zheng, Pengpeng Yu, et al.
Ore Geology Reviews (2024) Vol. 166, pp. 105928-105928
Open Access | Times Cited: 6
Fractal-Based Multi-Criteria Feature Selection to Enhance Predictive Capability of AI-Driven Mineral Prospectivity Mapping
Tao Sun, Mei Feng, Wenbin Pu, et al.
Fractal and Fractional (2024) Vol. 8, Iss. 4, pp. 224-224
Open Access | Times Cited: 5
Bayesian Decomposition Modelling: An Interpretable Nonlinear Approach for Mineral Prospectivity Mapping
Xiancheng Mao, Jinli Wang, Hao Deng, et al.
Mathematical Geosciences (2023) Vol. 55, Iss. 7, pp. 897-942
Closed Access | Times Cited: 13
Projection Pursuit Random Forest for Mineral Prospectivity Mapping
M.-L. Chen, Fan Xiao
Mathematical Geosciences (2023) Vol. 55, Iss. 7, pp. 963-987
Closed Access | Times Cited: 12
The world-class carbonate-hosted Fankou Zn-Pb deposit in China. Part I. Structural analysis: Evolutionary three-order thrusting structures control on the localization of Zn-Pb orebodies
Zhaobin Hu, Yi Zheng, Lanxuan Guo, et al.
Ore Geology Reviews (2023) Vol. 157, pp. 105463-105463
Open Access | Times Cited: 11
Combining numerical modeling and machine learning to predict mineral prospectivity: A case study from the Fankou Pb–Zn deposit, southern China
Fan Xiao, Xinyu Chen, Qiuming Cheng
Applied Geochemistry (2023) Vol. 160, pp. 105857-105857
Closed Access | Times Cited: 11
Mineral prospecting mapping with conditional generative adversarial network augmented data
Yixiao Wu, Bingli Liu, Yaxin Gao, et al.
Ore Geology Reviews (2023) Vol. 163, pp. 105787-105787
Open Access | Times Cited: 10
A Novel Multifractal Method for Geochemical Element Distribution Analysis
Mengyu Zhao, Yi Jin, Jiabin Dong, et al.
Natural Resources Research (2025)
Closed Access
Data-driven expeditious mapping and identifying granites in covered areas via deep machine learning: A case study on the implications for geodynamics and mineralization of Eastern Tianshan
Fan Xiao, Antony Tang, Huaqing Yang, et al.
Lithos (2025), pp. 107947-107947
Closed Access
MOGGP: A Novel Multi Objective Geometric Genetic Programming Model for Drought Forecasting
Ali Danandeh Mehr, Masood Jabarnejad, Mir Jafar Sadegh Safari
Physics and Chemistry of the Earth Parts A/B/C (2025), pp. 103879-103879
Closed Access
A semi-supervised learning framework for intelligent mineral prospectivity mapping: Incorporation of the CatBoost and Gaussian mixture model algorithms
Mahsa Hajihosseinlou, Abbas Maghsoudi, Reza Ghezelbash
Journal of Geochemical Exploration (2025), pp. 107755-107755
Closed Access
An Integrated Framework for Data-Driven Mineral Prospectivity Mapping Using Bagging-Based Positive-Unlabeled Learning and Bayesian Cost-Sensitive Logistic Regression
Zhiqiang Zhang, Gongwen Wang, Emmanuel John M. Carranza, et al.
Natural Resources Research (2022) Vol. 31, Iss. 6, pp. 3041-3060
Closed Access | Times Cited: 16
Three-dimensional mineral prospectivity mapping Considering structural restoration in the Dayingezhuang gold Deposit, eastern china
Jinli Wang, Xiancheng Mao, Zhankun Liu, et al.
Ore Geology Reviews (2024) Vol. 165, pp. 105860-105860
Open Access | Times Cited: 3
Geochemical Characteristics of Deep-Sea Sediments in Different Pacific Ocean Regions: Insights from Fractal Modeling
Yan Zhang, Gaowen He, Fan Xiao, et al.
Fractal and Fractional (2024) Vol. 8, Iss. 1, pp. 45-45
Open Access | Times Cited: 3
Deep multimodal fusion for 3D mineral prospectivity modeling: Integration of geological models and simulation data via canonical-correlated joint fusion networks
Yang Zheng, Hao Deng, Jingjie Wu, et al.
Computers & Geosciences (2024) Vol. 188, pp. 105618-105618
Closed Access | Times Cited: 3
GIS-based mineral prospectivity mapping using machine learning methods: A case study from Zhuonuo ore district, Tibet
Hongjun Cheng, Youye Zheng, Song Wu, et al.
Ore Geology Reviews (2023) Vol. 161, pp. 105627-105627
Open Access | Times Cited: 5
Mineralized-Anomaly Identification Based on Convolutional Sparse Autoencoder Network and Isolated Forest
Na Yang, Zhenkai Zhang, Jianhua Yang, et al.
Natural Resources Research (2022) Vol. 32, Iss. 1, pp. 1-18
Closed Access | Times Cited: 8
Using association rules analysis to determine favorable mineralization sites in the Jiaojia gold belt, Jiaodong Peninsula, East China
Xiancheng Mao, Miao Tang, Hao Deng, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 4
Manganese mineral prospectivity based on deep convolutional neural networks in Songtao of northeastern Guizhou
Kai Xu, Siyuan Zhao, Chonglong Wu, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1681-1697
Closed Access | Times Cited: 1
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