Sledovat
Katayoun Eshkofti
Katayoun Eshkofti
Postdoctoral fellow, KTH Royal Institute of Technology, Division of Decision and Control Systems
E-mailová adresa ověřena na: kth.se
Název
Citace
Citace
Rok
A gradient-enhanced physics-informed neural network (gPINN) scheme for the coupled non-fickian/non-fourierian diffusion-thermoelasticity analysis: A novel gPINN structure
K Eshkofti, SM Hosseini
Engineering Applications of Artificial Intelligence 126, 106908, 2023
62023
The novel PINN/gPINN-based deep learning schemes for non-Fickian coupled diffusion-elastic wave propagation analysis
K Eshkofti, SM Hosseini
Waves in Random and Complex Media, 1-24, 2023
32023
A deep learning approach based on the physics-informed neural networks for Gaussian thermal shock-induced thermoelastic wave propagation analysis in a thick hollow cylinder …
K Eshkofti, SM Hosseini
Waves in Random and Complex Media, 1-40, 2022
22022
Human Reliability Analysis for Cardiopulmonary Resuscitation Process in Emergency Medicine Using a Modified Hybrid Method Based on the Markov Model and Fault Tree Analysis
S Rasouli, K Eshkofti, SM Hosseini, E Pishbin
Journal of Patient Safety & Quality Improvement 9 (3), 163-175, 2021
12021
A new modified deep learning technique based on physics-informed neural networks (PINNs) for the shock-induced coupled thermoelasticity analysis in a porous material
K Eshkofti, SM Hosseini
Journal of Thermal Stresses 47 (6), 798-825, 2024
2024
Investigation of the Implementation of RFID Technology in Four-Echelon Supply Chain Simulation-Based Approach
S Shokouhyar, K Eshkofti, J Firouzbakht
Logistics Thought 14 (52), 159-187, 2015
2015
Systém momentálně nemůže danou operaci provést. Zkuste to znovu později.
Články 1–6