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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:

Intelligence Prediction of Some Selected Environmental Issues of Blasting: A Review
Bhatawdekar Ramesh Murlidhar, Danial Jahed Armaghani, Edy Tonnizam Mohamad
The Open Construction and Building Technology Journal (2020) Vol. 14, Iss. 1, pp. 298-308
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

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
Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance
Jie Zeng, Bishwajit Roy, Deepak Kumar, et al.
Engineering With Computers (2021) Vol. 38, Iss. S5, pp. 3811-3827
Closed Access | Times Cited: 89
Several Tree-Based Solutions for Predicting Flyrock Distance Due to Mine Blasting
Mojtaba Yari, Danial Jahed Armaghani, Chrysanthos Maraveas, et al.
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1345-1345
Open Access | Times Cited: 31
Air Pollution Risk Assessment Using a Hybrid Fuzzy Intelligent Probability-Based Approach: Mine Blasting Dust Impacts
Ezzeddin Bakhtavar, Shahab Hosseini, Kasun Hewage, et al.
Natural Resources Research (2021) Vol. 30, Iss. 3, pp. 2607-2627
Closed Access | Times Cited: 49
A Novel Combination of PCA and Machine Learning Techniques to Select the Most Important Factors for Predicting Tunnel Construction Performance
Jiangfeng Wang, Ahmed Salih Mohammed, Elżbieta Macioszek, et al.
Buildings (2022) Vol. 12, Iss. 7, pp. 919-919
Open Access | Times Cited: 36
Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Mohammed Ali Mohammed Al-Bared, Zahiraniza Mustaffa, Danial Jahed Armaghani, et al.
Transportation Geotechnics (2021) Vol. 30, pp. 100627-100627
Closed Access | Times Cited: 35
Predicting Ground Vibrations Due to Mine Blasting Using a Novel Artificial Neural Network-Based Cuckoo Search Optimization
Xuan-Nam Bui, Hoang Nguyen, Quang‐Hieu Tran, et al.
Natural Resources Research (2021) Vol. 30, Iss. 3, pp. 2663-2685
Closed Access | Times Cited: 33
A hybrid GEP and WOA approach to estimate the optimal penetration rate of TBM in granitic rock mass
Zimu Li, Behnam Yazdani Bejarbaneh, Panagiotis G. Asteris, et al.
Soft Computing (2021) Vol. 25, Iss. 17, pp. 11877-11895
Closed Access | Times Cited: 33
Estimating Flyrock Distance Induced Due to Mine Blasting by Extreme Learning Machine Coupled with an Equilibrium Optimizer
Ramesh Murlidhar Bhatawdekar, Radhikesh Kumar, Mohanad Muayad Sabri Sabri, et al.
Sustainability (2023) Vol. 15, Iss. 4, pp. 3265-3265
Open Access | Times Cited: 14
Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations
Parichehr Bayat, Masoud Monjezi, Amirhossein Mehrdanesh, et al.
Engineering With Computers (2021) Vol. 38, Iss. 4, pp. 3341-3350
Closed Access | Times Cited: 26
Predicting Blast-Induced Ground Vibration in Open-Pit Mines Using Different Nature-Inspired Optimization Algorithms and Deep Neural Network
Hoang Nguyen, Xuan-Nam Bui, Quang‐Hieu Tran, et al.
Natural Resources Research (2021) Vol. 30, Iss. 6, pp. 4695-4717
Closed Access | Times Cited: 22
A parametric study of ground vibration induced by quarry blasting: an application of group method of data handling
Jie Zeng, Ahmed Salih Mohammed, Fatemeh Mirzaei, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 4
Closed Access | Times Cited: 15
Prediction of Blast-Induced Ground Vibration at a Limestone Quarry: An Artificial Intelligence Approach
Clement Kweku Arthur, Ramesh Murlidhar Bhatawdekar, Edy Tonnizam Mohamad, et al.
Applied Sciences (2022) Vol. 12, Iss. 18, pp. 9189-9189
Open Access | Times Cited: 14
Assessment of Charge Initiation Techniques Effect on Blast Fragmentation and Environmental Safety: An Application of WipFrag Software
Blessing Olamide Taiwo, Yewuhalashet Fissha, Thomas Palangio, et al.
Mining (2023) Vol. 3, Iss. 3, pp. 532-551
Open Access | Times Cited: 7
Prediction of backbreak in hot strata/fiery seam of open-pit coal mine by decision tree and random forest algorithm
Mukul Sharma, Bhanwar Singh Choudhary, Hemant Agrawal
Arabian Journal of Geosciences (2022) Vol. 15, Iss. 15
Closed Access | Times Cited: 8
Development of mathematically motivated artificial intelligence models for the prediction of carbonate rock lime saturation factor for cement production
Blessing Olamide Taiwo, Niaz Muhammad Shahani, Akinwale Omosebi, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107444-107444
Closed Access | Times Cited: 4
Applications of AI and ML Techniques to Predict Backbreak and Flyrock Distance Resulting from Blasting
Ramesh Murlidhar Bhatawdekar, Danial Jahed Armaghani, Aydin Azizi
SpringerBriefs in applied sciences and technology (2021), pp. 41-59
Closed Access | Times Cited: 8
A Comprehensive Review of Rockmass Classification Systems for Assessing Blastability
Ramesh Murlidhar Bhatawdekar, A.K. Raina, Danial Jahed Armaghani
Lecture notes in civil engineering (2022), pp. 563-578
Closed Access | Times Cited: 5
Blast-induced flyrock
A.K. Raina, Ramesh Murlidhar Bhatawdekar
Elsevier eBooks (2022), pp. 209-247
Closed Access | Times Cited: 4
Review of Empirical and Intelligent Techniques for Evaluating Rock Fragmentation Induced by Blasting
Ramesh Murlidhar Bhatawdekar, Danial Jahed Armaghani, Aydin Azizi
SpringerBriefs in applied sciences and technology (2021), pp. 21-39
Closed Access | Times Cited: 5
Empirical, Statistical, and Intelligent Techniques for TBM Performance Prediction
Danial Jahed Armaghani, Aydin Azizi
SpringerBriefs in applied sciences and technology (2021), pp. 17-32
Closed Access | Times Cited: 4
Influence of admixtures on the performance of soundless chemical demolition agents and implications for their utilization
Nattamon Maneenoi, Raphael Bissen, Sakonvan Chawchai
Journal of Sustainable Mining (2022) Vol. 21, Iss. 2, pp. 93-111
Open Access | Times Cited: 3
Intelligent BIM Building Technology (BT) Based on Optimization Algorithm
Zhenzhen Geng
Lecture notes on data engineering and communications technologies (2023), pp. 693-702
Closed Access | Times Cited: 1
Application of Artificial Neural Networks for the Prediction of the Intensity of Ground Vibration at the Veliki Krivelj Copper Mine
Janić Snežana Radisavljević
Journal of Mining Science (2023) Vol. 59, Iss. 2, pp. 211-224
Closed Access | Times Cited: 1
An Overview of Blasting Operations and Possible Techniques to Solve Environmental Issues of Blasting
Ramesh Murlidhar Bhatawdekar, Danial Jahed Armaghani, Aydin Azizi
SpringerBriefs in applied sciences and technology (2021), pp. 1-19
Closed Access | Times Cited: 2
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