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Prediction of Geopolymer Concrete Compressive Strength Utilizing Artificial Neural Network and Nondestructive Testing Cover

Prediction of Geopolymer Concrete Compressive Strength Utilizing Artificial Neural Network and Nondestructive Testing

Civil and Environmental Engineering
Volume 18 (2022): Issue 2 (December 2022)
By: Hatem Almasaeid,  Abdelmajeed Alkasassbeh and  Bilal Yasin  
Open Access
|Dec 2022

Authors

Hatem Almasaeid

almasaeid.h@aabu.edu.jo

Civil Engineering Department, Al Al-Bayt University, Mafraq, Jordan

Abdelmajeed Alkasassbeh

Civil Engineering Department, Al Al-Bayt University, Mafraq, Jordan

Bilal Yasin

Civil Engineering Department, Al Al-Bayt University, Mafraq, Jordan
DOI: https://doi.org/10.2478/cee-2022-0060 | Journal eISSN: 2199-6512 | Journal ISSN: 1336-5835
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Language: English
Page range: 655 - 665
Published on: Dec 14, 2022
Published by: University of Žilina
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
Artificial neural network,
Geopolymer concrete,
Nondestructive test,
Ultrasonic pulse velocity,
Schmidt rebound hammer
Related subjects:
Business and economics,
Political economics,
Economic theory, systems and structures,
Business management,
Industries,
Environmental management

© 2022 Hatem Almasaeid, Abdelmajeed Alkasassbeh, Bilal Yasin, published by University of Žilina
This work is licensed under the Creative Commons Attribution 4.0 License.

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