Evaluating the strength of industrial wastesbased concrete reinforced with steel fiber using advanced machine learning.

The traditional evaluation of compressive strength through repeated experimental works can be resource-intensive, time-consuming, and environmentally taxing. Leveraging advanced machine learning (ML) offers a faster, cheaper, and more sustainable alternative for evaluating and optimizing concrete properties, particularly for materials incorporating industrial wastes and steel fibers. In this research work, a total of 166 records were collected and partitioned into training set (130 records = 80%) and validation set (36 records = 20%) in line with the requirements of data partitioning and sorting for optimal model performance.