1 citations · 2 across the 2 of their papers we have counts for
3 papers
math.OC2024★ 1 cited
KANtrol: A Physics-Informed Kolmogorov-Arnold Network Framework for Solving Multi-Dimensional and Fractional Optimal Control Problems
Alireza Afzal Aghaei
In this paper, we introduce the KANtrol framework, which utilizes Kolmogorov-Arnold Networks (KANs) to solve optimal control problems involving continuous time variables. We explai…
cs.LG2024★ 1 cited
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations
Alireza Afzal Aghaei
This paper introduces a novel methodology for solving distributed-order fractional differential equations using a physics-informed machine learning framework. The core of this appr…
cs.LG2024
PINNIES: An Efficient Physics-Informed Neural Network Framework to Integral Operator Problems
Alireza Afzal Aghaei, Mahdi Movahedian Moghaddam, Kourosh Parand
This paper introduces an efficient tensor-vector product technique for the rapid and accurate approximation of integral operators within physics-informed deep learning frameworks.…