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.

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Showing 1-25 of 31 citing articles:

Prediction of the Mechanical Properties of Basalt Fiber Reinforced High-Performance Concrete Using Machine Learning Techniques
Ali Hasanzadeh, Nikolai Vatin, Mohammad Hematibahar, et al.
Materials (2022) Vol. 15, Iss. 20, pp. 7165-7165
Open Access | Times Cited: 48

New neural network-based algorithm for predicting fatigue life of aluminum alloys in terms of machining parameters
Kazem Reza Kashyzadeh, Siamak Ghorbani
Engineering Failure Analysis (2023) Vol. 146, pp. 107128-107128
Closed Access | Times Cited: 28

Novel GA-Based DNN Architecture for Identifying the Failure Mode with High Accuracy and Analyzing Its Effects on the System
Naeim Rezaeian, Regina Gurina, О. А. Салтыкова, et al.
Applied Sciences (2024) Vol. 14, Iss. 8, pp. 3354-3354
Open Access | Times Cited: 12

Predicting mechanical properties of self-healing concrete with Trichoderma Reesei Fungus using machine learning
Paschal Chimeremeze Chiadighikaobi, Mohammad Hematibahar, Махмуд Харун, et al.
Cogent Engineering (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 10

Comparative study of different machine learning approaches for predicting the compressive strength of palm fuel ash concrete
Yasmina Kellouche, Bassam A. Tayeh, Yazid Chetbani, et al.
Journal of Building Engineering (2024) Vol. 88, pp. 109187-109187
Closed Access | Times Cited: 8

Assessment of Concrete Compressive Strength by Destructive Testing: Influence of Strength Correction Factors and Size Effect
Adel Benidir
Advances in science and technology (2025) Vol. 159, pp. 13-18
Closed Access

A Critical Review on Improving the Fatigue Life and Corrosion Properties of Magnesium Alloys via the Technique of Adding Different Elements
Kazem Reza Kashyzadeh, Nima Amiri, Erfan Maleki, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 3, pp. 527-527
Open Access | Times Cited: 15

A critical analysis of compressive strength prediction of glass fiber and carbon fiber reinforced concrete over machine learning models
K. K. Yaswanth, V. S. Vani, Krupasindhu Biswal, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access

The Prediction of Compressive Strength and Compressive Stress–Strain of Basalt Fiber Reinforced High-Performance Concrete Using Classical Programming and Logistic Map Algorithm
Mohammad Hematibahar, Nikolai Vatin, Hayder Abbas Ashour Alaraza, et al.
Materials (2022) Vol. 15, Iss. 19, pp. 6975-6975
Open Access | Times Cited: 25

PREDICTION OF CONCRETE MIXTURE DESIGN AND COMPRESSIVE STRENGTH THROUGH DATA ANALYSIS AND MACHINE LEARNING
Mohammad Hematibahar
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES (2024) Vol. 19, Iss. 3
Open Access | Times Cited: 3

Improvement of HCF life of automotive safety components considering a novel design of wheel alignment based on a Hybrid multibody dynamic, finite element, and data mining techniques
Kazem Reza Kashyzadeh, G.H. Farrahi
Engineering Failure Analysis (2022) Vol. 143, pp. 106932-106932
Closed Access | Times Cited: 12

Influence of the ANN Hyperparameters on the Forecast Accuracy of RAC’s Compressive Strength
Talita Andrade da Costa Almeida, Emerson Felipe Félix, Carlos Manuel Andrade de Sousa, et al.
Materials (2023) Vol. 16, Iss. 24, pp. 7683-7683
Open Access | Times Cited: 7

A Novel Approach for Analyzing the Effects of Almen Intensity on the Residual Stress and Hardness of Shot-Peened (TiB + TiC)/Ti–6Al–4V Composite: Deep Learning
Erfan Maleki, Okan Ünal, Seyed Mahmoud Seyedi Sahebari, et al.
Materials (2023) Vol. 16, Iss. 13, pp. 4693-4693
Open Access | Times Cited: 6

Advancements in Gas Turbine Fault Detection: A Machine Learning Approach Based on the Temporal Convolutional Network–Autoencoder Model
Al-Tekreeti Watban Khalid Fahmi, Kazem Reza Kashyzadeh, Siamak Ghorbani
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4551-4551
Open Access | Times Cited: 1

Laboratory investigation and BP neural network modeling on heat-activated oil shale semi-coke attributable to the mechanical properties of concrete
Bo Li, Jiadong Wang, Gui Cao, et al.
Case Studies in Construction Materials (2023) Vol. 18, pp. e02090-e02090
Open Access | Times Cited: 3

Back analysis of shear strength parameters of slope based on BP neural network and genetic algorithm
Xiaopeng Deng, Xinghua Xiang
Engineering Reports (2024) Vol. 6, Iss. 10
Closed Access


Mohammad Hematibahar, Махмуд Харун
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES (2024) Vol. 19, Iss. 3
Open Access

Enhanced Autoregressive Integrated Moving Average Model for Anomaly Detection in Power Plant Operations
Aliya Fahmi, Kazem Reza Kashyzadeh, Siamak Ghorbani
International journal of engineering. Transactions B: Applications (2024) Vol. 37, Iss. 8, pp. 1691-1699
Open Access

Tensile Properties Estimation of 3D Printed Polylactic Acid Samples via Process Parameters using Data-Driven Methods
Abdesselem Said, Siamak Ghorbani, Kazem Reza Kashyzadeh
(2024) Vol. 117, pp. 1-6
Closed Access

A methodological study of slump prediction and optimisation of radioprotective serpentine concrete
Hongle Li, Jianjun Shi, Hongle Li, et al.
Construction and Building Materials (2024) Vol. 451, pp. 138706-138706
Closed Access

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