Machine learning approach for predicting the compressive strength of biomedical waste ash in concrete: a sustainability approach

Machine learning approach for predicting the compressive strength of biomedical waste ash in concrete: a sustainability approach

Abstract This study investigates the effects of strength and durability of concrete for different water-cement ratios, aggregate contents, and partial replacement of biomedical waste ash at 5%, 10%, 15%, 20%, and 25% by weight of cement. At 7, 14, and 28 days, the control mix showed inferior mechani...

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Bibliographic Details
Main Authors: Rakesh Kumar, S. Karthik, Abhishek Kumar, Adithya Tantri, Shahaji, S. Sathvik
Format: Article
Language:English
Published: Springer 2025-02-01
Series:Discover Materials
Subjects:
Biomedical waste
Mechanical properties
Durability properties
Prediction
Random forest
K-nearest neighbor
Online Access:https://doi.org/10.1007/s43939-025-00223-9
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https://doi.org/10.1007/s43939-025-00223-9

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