Prediction of properties of steel alloys
This work addresses property prediction for steel alloys, which is incremental as it applies existing methods to new data without introducing novel techniques.
The study tackled predicting four mechanical properties of industrially used steel alloys using four supervised machine learning models, achieving results based on an experimental database from the literature.
We present a study of possible predictors based on four supervised machine learning models for the prediction of four mechanical properties of the main industrially used steels. The results were obtained from an experimental database available in the literature which were used as input to train and evaluate the models.