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Prediction of SMA Hysteresis Behavior: A Deep Learning Approach with Explainable AI

Year: 2026

Type: article

Abstract: This article presents an approach to predicting the hysteresis behavior of shape memory alloys (SMAs) using a Temporal Convolutional Network (TCN) deep learning model, followed by the interpretation of the results using Expla... | Find, read and cite all the research you need on Tech Science Press

Source: Computers, materials & continua/Computers, materials & continua (Print)

DOI: 10.32604/cmc.2026.077062

Authors: Dmytro Tymoshchuk, Oleh Yasniy, Iryna Didych, Pavlo Maruschak, Yuri Lapusta

Institutions: Centre National de la Recherche Scientifique, Institut Pascal, Université Clermont Auvergne, Ternopil Ivan Pului National Technical University, Clermont Auvergne INP

Language: English

Topic: Shape Memory Alloy Transformations

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W7127639255

FWCI: 3.336

Cites:

Cited by: 3

Related to: 10