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:

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms
Chengyu Xie, Hoang Nguyen, Xuan-Nam Bui, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101108-101108
Open Access | Times Cited: 73

Showing 1-25 of 73 citing articles:

Optimization of random forest through the use of MVO, GWO and MFO in evaluating the stability of underground entry-type excavations
Jian Zhou, Shuai Huang, Yingui Qiu
Tunnelling and Underground Space Technology (2022) Vol. 124, pp. 104494-104494
Closed Access | Times Cited: 99
Employing a genetic algorithm and grey wolf optimizer for optimizing RF models to evaluate soil liquefaction potential
Jian Zhou, Shuai Huang, Tao Zhou, et al.
Artificial Intelligence Review (2022) Vol. 55, Iss. 7, pp. 5673-5705
Closed Access | Times Cited: 96
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: 23
A novel systematic and evolved approach based on XGBoost-firefly algorithm to predict Young’s modulus and unconfined compressive strength of rock
Jing Cao, Juncheng Gao, Hima Nikafshan Rad, et al.
Engineering With Computers (2021) Vol. 38, Iss. S5, pp. 3829-3845
Closed Access | Times Cited: 91
A Novel Hunger Games Search Optimization-Based Artificial Neural Network for Predicting Ground Vibration Intensity Induced by Mine Blasting
Hoang Nguyen, Xuan-Nam Bui
Natural Resources Research (2021) Vol. 30, Iss. 5, pp. 3865-3880
Closed Access | Times Cited: 61
Predicting triaxial compressive strength of high-temperature treated rock using machine learning techniques
Xunjian Hu, Junjie Shentu, Ni Xie, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 15, Iss. 8, pp. 2072-2082
Open Access | Times Cited: 60
Six Novel Hybrid Extreme Learning Machine–Swarm Intelligence Optimization (ELM–SIO) Models for Predicting Backbreak in Open-Pit Blasting
Chuanqi Li, Jian Zhou, Manoj Khandelwal, et al.
Natural Resources Research (2022) Vol. 31, Iss. 5, pp. 3017-3039
Open Access | Times Cited: 49
Cross-correlation stacking-based microseismic source location using three metaheuristic optimization algorithms
Jian Zhou, Xiaojie Shen, Yingui Qiu, et al.
Tunnelling and Underground Space Technology (2022) Vol. 126, pp. 104570-104570
Closed Access | Times Cited: 48
XG Boost Algorithm to Simultaneous Prediction of Rock Fragmentation and Induced Ground Vibration Using Unique Blast Data
N. Sri Chandrahas, Bhanwar Singh Choudhary, M. Vishnu Teja, et al.
Applied Sciences (2022) Vol. 12, Iss. 10, pp. 5269-5269
Open Access | Times Cited: 43
Predicting and validating the load-settlement behavior of large-scale geosynthetic-reinforced soil abutments using hybrid intelligent modeling
Muhammad Nouman Amjad Raja, Syed Taseer Abbas Jaffar, Abidhan Bardhan, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 15, Iss. 3, pp. 773-788
Open Access | Times Cited: 43
Prediction of ground vibration due to mine blasting in a surface lead–zinc mine using machine learning ensemble techniques
Shahab Hosseini, Rashed Pourmirzaee, Danial Jahed Armaghani, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 38
Estimating dynamic compressive strength of rock subjected to freeze-thaw weathering by data-driven models and non-destructive rock properties
Shengtao Zhou, Yu Lei, Zong‐Xian Zhang, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-24
Closed Access | Times Cited: 12
Automated Scene-Adaptive Rock Fragment Recognition Based on the Enhanced Segment Anything Model and Fine-Tuning RTMDet
Yudi Tang, Yulin Wang, Xin Wang, et al.
Rock Mechanics and Rock Engineering (2025)
Open Access | Times Cited: 1
Performance of Hybrid SCA-RF and HHO-RF Models for Predicting Backbreak in Open-Pit Mine Blasting Operations
Jian Zhou, Yong Dai, Manoj Khandelwal, et al.
Natural Resources Research (2021) Vol. 30, Iss. 6, pp. 4753-4771
Closed Access | Times Cited: 55
A novel improved Harris Hawks optimization algorithm coupled with ELM for predicting permeability of tight carbonates
Navid Kardani, Abidhan Bardhan, Bishwajit Roy, et al.
Engineering With Computers (2021) Vol. 38, Iss. S5, pp. 4323-4346
Closed Access | Times Cited: 49
Advances in Blast-Induced Impact Prediction—A Review of Machine Learning Applications
Nelson Kofi Dumakor-Dupey, Sampurna Arya, Ankit Jha
Minerals (2021) Vol. 11, Iss. 6, pp. 601-601
Open Access | Times Cited: 43
A Kernel Extreme Learning Machine-Grey Wolf Optimizer (KELM-GWO) Model to Predict Uniaxial Compressive Strength of Rock
Chuanqi Li, Jian Zhou, Daniel Dias, et al.
Applied Sciences (2022) Vol. 12, Iss. 17, pp. 8468-8468
Open Access | Times Cited: 34
Optimized ANN-based approach for estimation of shear strength of soil
Ahsan Rabbani, Pijush Samui, Sunita Kumari
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 8, pp. 3627-3640
Closed Access | Times Cited: 20
Review of machine learning application in mine blasting
Ahmed Abd Elwahab, Erkan Topal, Hyongdoo Jang
Arabian Journal of Geosciences (2023) Vol. 16, Iss. 2
Open Access | Times Cited: 18
Experimental data – driven algorithm to predict muckpile characteristics in jointed overburden bench using unmanned aerial vehicle and AI tools
N. Sri Chandrahas, Yewuhalashet Fissha, Bhanwar Singh Choudhary, et al.
International Journal of Mining Reclamation and Environment (2024) Vol. 38, Iss. 8, pp. 642-676
Closed Access | Times Cited: 8
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: 7
Improved Levenberg–Marquardt backpropagation neural network by particle swarm and whale optimization algorithms to predict the deflection of RC beams
Jue Zhao, Hoang Nguyen, T. Nguyen‐Thoi, et al.
Engineering With Computers (2021) Vol. 38, Iss. S5, pp. 3847-3869
Closed Access | Times Cited: 40
Enhancing the performance of tunnel water inflow prediction using Random Forest optimized by Grey Wolf Optimizer
Jian Zhou, Yulin Zhang, Chuanqi Li, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 3, pp. 2405-2420
Closed Access | Times Cited: 15
Application of Artificial Neural Network (ANN) for Prediction and Optimization of Blast-Induced Impacts
Ali Y. Al-Bakri, Mohammed Sazid
Mining (2021) Vol. 1, Iss. 3, pp. 315-334
Open Access | Times Cited: 32
A novel ensemble machine learning model to predict mine blasting–induced rock fragmentation
Mojtaba Yari, Biao He, Danial Jahed Armaghani, et al.
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 5
Closed Access | Times Cited: 12
Page 1 - Next Page

Scroll to top