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Intelligent Models for Prediction of Compressive Strength of Geopolymer Pervious Concrete Hybridized with Agro-Industrial and Construction-Demolition Wastes Cover

Intelligent Models for Prediction of Compressive Strength of Geopolymer Pervious Concrete Hybridized with Agro-Industrial and Construction-Demolition Wastes

Studia Geotechnica et Mechanica
Volume 46 (2024): Issue s1 (December 2024)
By: Shriram Marathe and  Anisha P Rodrigues  
Open Access
|Sep 2024

Authors

Shriram Marathe

shriram.marathe@pwr.edu.pl

Department of Materials Engineering and Construction Processes, Faculty of Civil Engineering, Wrocław University of Science and Technology, Wrocław, Poland

Anisha P Rodrigues

Department of Computer Science and Engineering, Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), INDIA
DOI: https://doi.org/10.2478/sgem-2024-0020 | Journal eISSN: 2083-831X | Journal ISSN: 0137-6365
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Language: English
Page range: 349 - 376
Submitted on: May 7, 2024
Accepted on: Jul 15, 2024
Published on: Sep 26, 2024
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Compressive Strength,
Agro-Industrial Wastes,
Machine Learning,
Geopolymer,
Pervious Concrete
Related subjects:
Geosciences,
Geosciences, other,
Materials sciences,
Composites,
Porous materials,
Physics,
Mechanics and fluid dynamics

© 2024 Shriram Marathe, Anisha P Rodrigues, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution 4.0 License.

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