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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

J. Abellán-García

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Review Open access Oct 2026

Machine Learning-Based prediction of flexural strength in recycledaggregate concrete: a K-Nearest Neighbors approach

Predicting the flexural strength of recycled aggregate concrete (RAC) is challenging because recycled constituents introduce variability and nonlinear interactions. This study develops a K-nearest neighbors (KNN) model to predict 90-day flexural strength using 366 mix designs collected from peer-reviewed studies publis...

Jesús D. Escalante-Tovar, Keldys D. Sarmiento-Pupo, Jesús E. Altamiranda et al. · 0 citations
Open access Sep 2026

Machine Learning Prediction of 28-Day Compressive Strength in Recycled Aggregate Concretes with Supplementary Cementitious Materials: Experimental Validation Using Metakaolin and Spent Fluid Catalytic Cracking Catalyst Residue

This study develops an interpretable machine learning framework for predicting the 28-day compressive strength of recycled aggregate concrete containing supplementary cementitious materials and validates it experimentally using metakaolin and spent fluid catalytic cracking catalyst residue. A broad multi-source databas...

Jesús E. Altamiranda-Ramos, L. Castillo-Suárez, J. Abellán-García · 1 citation
Open access Jul 2026

XGBoost-Based Prediction of 28-Day Flexural Strength in Recycled Aggregate Concrete with Supplementary Cementitious Materials

The applied design of recycled aggregate concrete (RAC) with supplementary cementitious materials (SCMs) requires reliable estimation of 28-day flexural strength (FS28) before trial batching. This is challenging because RAC–SCM mixtures involve nonlinear interactions among binder chemistry, aggregate replacement, water...

Jesús E. Altamiranda-Ramos, Alejandro Molina-Chegwin, Pau Coma-Busquets et al. · 0 citations

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