Artificial neural networks based optimization techniques: A review

MGM Abdolrasol, SMS Hussain, TS Ustun, MR Sarker… - Electronics, 2021 - mdpi.com
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …

[HTML][HTML] Artificial neural networks: a practical review of applications involving fractional calculus

E Viera-Martin, JF Gómez-Aguilar… - The European Physical …, 2022 - Springer
In this work, a bibliographic analysis on artificial neural networks (ANNs) using fractional
calculus (FC) theory has been developed to summarize the main features and applications …

Numerical investigations on COVID‐19 model through singular and non‐singular fractional operators

S Kumar, RP Chauhan, S Momani… - Numerical Methods for …, 2024 - Wiley Online Library
Nowadays, the complete world is suffering from untreated infectious epidemic disease
COVID‐19 due to coronavirus, which is a very dangerous and deadly viral infection. So, the …

A novel numerical approach for time-varying impulsive fractional differential equations using theory of functional connections and neural network

SM Sivalingam, V Govindaraj - Expert Systems with Applications, 2024 - Elsevier
In this paper, we propose a physics-informed neural network-based scheme to solve time-
varying impulsive fractional differential equations without any labeled data. At first, the …

Neuro-heuristics for nonlinear singular Thomas-Fermi systems

Z Sabir, MA Manzar, MAZ Raja, M Sheraz… - Applied Soft …, 2018 - Elsevier
A neuro-heuristic scheme is design to solve nonlinear singular second order system based
on Thomas-Fermi equation using the strength of universal approximation capabilities of …

[HTML][HTML] A novel design of fractional Meyer wavelet neural networks with application to the nonlinear singular fractional Lane-Emden systems

Z Sabir, MAZ Raja, JLG Guirao, M Shoaib - Alexandria Engineering Journal, 2021 - Elsevier
In this study, a novel stochastic computational frameworks based on fractional Meyer
wavelet artificial neural network (FMW-ANN) is designed for nonlinear-singular fractional …

A neuro-swarming intelligence-based computing for second order singular periodic non-linear boundary value problems

Z Sabir, MAZ Raja, JLG Guirao, M Shoaib - Frontiers in Physics, 2020 - frontiersin.org
In the present investigation, a novel neuro-swarming intelligence-based numerical
computing solver is developed for solving second order non-linear singular periodic (NSP) …

A novel optimization-based physics-informed neural network scheme for solving fractional differential equations

S SM, P Kumar, V Govindaraj - Engineering with Computers, 2024 - Springer
Nowadays, the study of neural networks is one of the most interesting research topics. In this
article, we introduce a novel scheme based on Physics Informed Neural Network (PINN) for …

[HTML][HTML] Investigation of fractal-fractional order model of COVID-19 in Pakistan under Atangana-Baleanu Caputo (ABC) derivative

M Arfan, H Alrabaiah, MU Rahman, YL Sun… - Results in Physics, 2021 - Elsevier
This manuscript addressing the dynamics of fractal-fractional type modified SEIR model
under Atangana-Baleanu Caputo (ABC) derivative of fractional order y and fractal dimension …

A neural networks-based numerical method for the generalized Caputo-type fractional differential equations

SM Sivalingam, P Kumar, V Govindaraj - Mathematics and Computers in …, 2023 - Elsevier
The paper presents a numerical technique based on neural networks for generalized
Caputo-type fractional differential equations with and without delay. We employ the theory of …