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Machine learning insights into the strain-stress behavior of nitinol alloys at low temperatures: Utilizing the orange data mining tool

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Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Ahead of Print.
This study entails a new technique, based on machine learning algorithms, for predicting the strain-stress behavior of Nitinol alloys. The study utilizes Orange data mining software to determine if algorithms like Linear Regression, Random Forest, k-...