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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:

Rock Strain Prediction Using Deep Neural Network and Hybrid Models of ANFIS and Meta-Heuristic Optimization Algorithms
T. Pradeep, Abidhan Bardhan, Avijit Burman, et al.
Infrastructures (2021) Vol. 6, Iss. 9, pp. 129-129
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Prediction of probability of liquefaction using hybrid ANN with optimization techniques
Divesh Ranjan Kumar, Pijush Samui, Avijit Burman
Arabian Journal of Geosciences (2022) Vol. 15, Iss. 20
Closed Access | Times Cited: 36
State of art soft computing based simulation models for bearing capacity of pile foundation: a comparative study of hybrid ANNs and conventional models
Manish Kumar, Vinay Kumar, Balaji Ganesh Rajagopal, et al.
Modeling Earth Systems and Environment (2022) Vol. 9, Iss. 2, pp. 2533-2551
Closed Access | Times Cited: 30
Liquefaction susceptibility using machine learning based on SPT data
Divesh Ranjan Kumar, Pijush Samui, Avijit Burman, et al.
Intelligent Systems with Applications (2023) Vol. 20, pp. 200281-200281
Open Access | Times Cited: 18
Ameliorated Golden jackal optimization (AGJO) with enhanced movement and multi-angle position updating strategy for solving engineering problems
Jianfu Bai, Samir Khatir, Laith Abualigah, et al.
Advances in Engineering Software (2024) Vol. 194, pp. 103665-103665
Open Access | Times Cited: 7
Comparative and parametric study of AI-based models for risk assessment against soil liquefaction for high-intensity earthquakes
Sufyan Ghani, Sunita Kumari, Sagar Jaiswal, et al.
Arabian Journal of Geosciences (2022) Vol. 15, Iss. 14
Closed Access | Times Cited: 23
Prediction of Rock Strain Using Hybrid Approach of Ann and Optimization Algorithms
T. Pradeep, Pijush Samui
Geotechnical and Geological Engineering (2022) Vol. 40, Iss. 9, pp. 4617-4643
Closed Access | Times Cited: 22
Deep learning-based activity-aware 3D human motion trajectory prediction in construction
Moein Younesi Heravi, Youjin Jang, Inbae Jeong, et al.
Expert Systems with Applications (2023) Vol. 239, pp. 122423-122423
Closed Access | Times Cited: 14
Advanced machine learning approaches for uniaxial compressive strength prediction of Indian rocks using petrographic properties
Md Shayan Sabri, Amit Jaiswal, A. K. Verma, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 6, pp. 5265-5286
Closed Access | Times Cited: 5
A novel approach for assessment of seismic induced liquefaction susceptibility of soil
Divesh Ranjan Kumar, Pijush Samui, Avijit Burman, et al.
Journal of Earth System Science (2024) Vol. 133, Iss. 3
Closed Access | Times Cited: 4
Seismically Induced Liquefaction Potential Assessment by Different Artificial Intelligence Procedures
Divesh Ranjan Kumar, Pijush Samui, Avijit Burman, et al.
Transportation Infrastructure Geotechnology (2023) Vol. 11, Iss. 3, pp. 1272-1293
Closed Access | Times Cited: 11
Implementation of hybrid wind speed prediction model based on different data mining and signal processing approaches
Okan Mert Katipoğlu
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 23, pp. 64589-64605
Closed Access | Times Cited: 9
Optimized ANN-based surrogate models for evaluating the stability of trapdoors in Hoek‒Brown rock masses
Kongtawan Sangjinda, Suraparb Keawsawasvong, Pitthaya Jamsawang, et al.
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access | Times Cited: 3
Comparison of different optimized machine learning algorithms for daily river flow forecasting
Pijush Samui, Sefa Nur Yeşilyurt, Yıldırım Dalkiliç, et al.
Earth Science Informatics (2022) Vol. 16, Iss. 1, pp. 533-548
Closed Access | Times Cited: 15
Hybrid Ensemble Model for Predicting the Strength of FRP Laminates Bonded to the Concrete
Anas Abdulalem Alabdullh, Rahul Biswas, Jitendra Gudainiyan, et al.
Polymers (2022) Vol. 14, Iss. 17, pp. 3505-3505
Open Access | Times Cited: 14
Probabilistic analysis of gravity retaining wall against bearing failure
Rashid Mustafa, Pijush Samui, Sunita Kumari, et al.
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 8, pp. 3099-3119
Closed Access | Times Cited: 8
Prediction of the Soil Permeability Coefficient of Reservoirs Using a Deep Neural Network Based on a Dendrite Concept
Myeonghwan Kim, Chul Min Song
Processes (2023) Vol. 11, Iss. 3, pp. 661-661
Open Access | Times Cited: 7
Modelling Compression Strength of Waste PET and SCM Blended Cementitious Grout Using Hybrid of LSSVM Models
Kaffayatullah Khan, Jitendra Gudainiyan, Mudassir Iqbal, et al.
Materials (2022) Vol. 15, Iss. 15, pp. 5242-5242
Open Access | Times Cited: 9
Ensemble unit and AI techniques for prediction of rock strain
T. Pradeep, Pijush Samui, Navid Kardani, et al.
Frontiers of Structural and Civil Engineering (2022) Vol. 16, Iss. 7, pp. 858-870
Closed Access | Times Cited: 9
ANN- PSO modelling for predicting buckling of self-compacting concrete column containing RHA properties
Abdul Bari Jabar, T. Pradeep
Matéria (Rio de Janeiro) (2023) Vol. 28, Iss. 2
Open Access | Times Cited: 5
State-Of-The-Art ML-Based Prediction Models for Metakaolin-Based Mortar Using ELM and GMDH
Manish Kumar, Ranjana Anand, Krishna Deep, et al.
Lecture notes in civil engineering (2024), pp. 179-188
Closed Access | Times Cited: 1
A Hybrid SVR-Based Prediction Model for the Interfacial Bond Strength of Externally Bonded FRP Laminates on Grooves with Concrete Prisms
Kaffayatullah Khan, Mudassir Iqbal, Rahul Biswas, et al.
Polymers (2022) Vol. 14, Iss. 15, pp. 3097-3097
Open Access | Times Cited: 7
Analysis of the Performance of a Hybrid Thermal Power Plant Using Adaptive Neuro-Fuzzy Inference System (ANFIS)-Based Approaches
Kantu Thomas Kabengele, Isaac Oyeyemi Olayode, Lagouge K. Tartibu
Applied Sciences (2023) Vol. 13, Iss. 21, pp. 11874-11874
Open Access | Times Cited: 3
Prediction of compressive strength of granite: use of machine learning techniques and intelligent system
Zhi Yu, Jian Zhou, HU Liu-qing
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 4113-4129
Closed Access | Times Cited: 3
A Semisupervised Just-In-Time Learning Framework Based on Local Label Propagation and Its Application to Industrial Virtual Sensing
Ping Wang, Yichao Yin, Junxi Zhou, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 20, pp. 24983-24992
Closed Access | Times Cited: 2
Optimized machine learning approach for structural response prediction using wolf-bird optimizer
Mahdi Azizi, Annan Zhou
Structures (2024) Vol. 65, pp. 106691-106691
Open Access
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