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Journal Editing.... by Mega nathan is a document available to read on EtoBox.

This study presents a machine learning platform for predicting concrete compressive strength using a dataset of 1030 concrete mix samples. Various regression models were evaluated, with the XG Boost model demonstrating the best performance, achieving a test R² of 0.9125. The research integrates traditional civil engineering practices with machine learning techniques to enhance prediction accuracy and reliability.

Author
Mega nathan
Language
EN