@article{paperid:1095446,
author = {Eshkofti, Katayoun and Hosseini, Seyed Mahmoud},
title = {A gradient-enhanced physics-informed neural network (gPINN) scheme for the coupled non-fickian/non-fourierian diffusion-thermoelasticity analysis: A novel gPINN structure},
journal = {Engineering Applications of Artificial Intelligence},
year = {2023},
volume = {126},
number = {1},
month = {November},
issn = {0952-1976},
pages = {106908--106908},
			numpages = {0},
keywords = {Gradient-enhanced physics-informed neural; network (gPINN); Non-Fick diffusion; Thermoelasticity; Lord-Shulman theory; Partial differential equations (PDEs).},
}