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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:

State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting
Jian Zhou, Yulin Zhang, Yingui Qiu
Artificial Intelligence Review (2024) Vol. 57, Iss. 1
Open Access | Times Cited: 18

Showing 18 citing articles:

Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms
Yewuhalashet Fissha, Jitendra Khatti, Hajime Ikeda, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 12
增强采矿作业中岩石碎片预测: 利用混合GWO-RF模型及SHAP可解释性分析
Yulin Zhang, Yingui Qiu, Danial Jahed Armaghani, et al.
Journal of Central South University (2024) Vol. 31, Iss. 8, pp. 2916-2929
Closed Access | Times Cited: 7
Enhanced multi-task learning models for pile drivability prediction: Leveraging metaheuristic algorithms and statistical evaluation
Zhenyu Wang, Jian Zhou, Kun Du, et al.
Transportation Geotechnics (2024) Vol. 47, pp. 101288-101288
Closed Access | Times Cited: 5
Optimization of an Artificial Neural Network Using Four Novel Metaheuristic Algorithms for the Prediction of Rock Fragmentation in Mine Blasting
Ahsan Rabbani, Divesh Ranjan Kumar, Yewuhalashet Fissha, et al.
Journal of The Institution of Engineers (India) Series D (2024)
Closed Access | Times Cited: 5
Analysis of Intelligent Mining Pressure Monitoring and Surface Displacement Intelligent Methods Based on Machine Learning Algorithms
Qiming Wei, Ya-Jun Hu, Hu Wang, et al.
Sustainable civil infrastructures (2025), pp. 123-133
Closed Access
Drill Pattern Optimisation for Large Complex Blasts to Improve Fragmentation and Dig Efficiency
Ozan Perincek, Ryan Loxton, S. M. Kulkarni, et al.
Mathematical Geosciences (2025)
Open Access
A novel hybrid machine learning and explainable artificial intelligence approaches for improved source rock prediction and hydrocarbon potential in the Mandawa Basin, SE Tanzania
Christopher N. Mkono, Chuanbo Shen, Alvin K. Mulashani, et al.
International Journal of Coal Geology (2025), pp. 104699-104699
Closed Access
A black-winged kite optimization algorithm enhanced by osprey optimization and vertical and horizontal crossover improvement
Yancang Li, Baidi Shi, Wei Qiao, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A Visual Survey of Tunnel Boring Machine (TBM) Performance in Tunneling Excavation: Mainstream Direction, Brief Review and Future Prospects
Yulin Zhang, Jian Zhou, Yingui Qiu, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4512-4512
Open Access | Times Cited: 4
A comprehensive study on the application of soft computing methods in predicting and evaluating rock fragmentation in an opencast mining
Ahsan Rabbani, Hanan Samadi, Yewuhalashet Fissha, et al.
Earth Science Informatics (2024)
Closed Access | Times Cited: 3
Borehole Breakout Prediction Based on Multi-Output Machine Learning Models Using the Walrus Optimization Algorithm
Rui Zhang, Jian Zhou, Ming Tao, et al.
Applied Sciences (2024) Vol. 14, Iss. 14, pp. 6164-6164
Open Access | Times Cited: 2
Mean Block Size Prediction in Rock Blast Fragmentation Using TPE-Tree-Based Model Approach with SHapley Additive exPlanations
Madalitso Mame, Yingui Qiu, Shuai Huang, et al.
Mining Metallurgy & Exploration (2024) Vol. 41, Iss. 5, pp. 2325-2340
Closed Access | Times Cited: 2
Comprehensive review and future perspectives on prediction and mitigation of tunnel-induced ground settlement: A bibliometric analysis and methodological overview (2002–2022)
Jian Zhou, Hongning Qi, Kang Peng, et al.
Tunnelling and Underground Space Technology (2024) Vol. 154, pp. 106081-106081
Open Access | Times Cited: 2
Data-driven machine learning approaches for simultaneous prediction of peak particle velocity and frequency induced by rock blasting in mining
Yewuhalashet Fissha, Prashanth Ragam, Hajime Ikeda, et al.
Rock Mechanics Bulletin (2024), pp. 100166-100166
Open Access | Times Cited: 2
Machine learning for open-pit mining: a systematic review
Shi Qiang Liu, Lizhu Liu, Erhan Kozan, et al.
International Journal of Mining Reclamation and Environment (2024), pp. 1-39
Closed Access | Times Cited: 1
Chaos Game Optimization-Hybridized Artificial Neural Network for Predicting Blast-Induced Ground Vibration
Shugang Zhao, Liguan Wang, Mingyu Cao
Applied Sciences (2024) Vol. 14, Iss. 9, pp. 3759-3759
Open Access
Knowledge structure and research progress in earthquake-induced liquefaction assessment from 2000 to 2023: A scientometric analysis incorporating domain knowledge
Hongning Qi, Jian Zhou, Kang Peng, et al.
Soil Dynamics and Earthquake Engineering (2024) Vol. 188, pp. 109075-109075
Closed Access
Study on the Influence of Notched Empty Hole Parameters on Directional Fracture Blasting Effect
Xiantang Zhang, Rongyan Ma, Yong Yang, et al.
Buildings (2024) Vol. 14, Iss. 12, pp. 4077-4077
Open Access
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