Exploring new traveling wave solutions by solving the nonlinear space–time fractal Fornberg−Whitham equation DOI Creative Commons

Akbar Nazari-Golshan

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 12, 2024

Complex and nonlinear fractal equations are ubiquitous in natural phenomena. This research employs the Euler−Lagrange semi-inverse methods to derive space–time Fornberg–Whitham equation. derivation provides an in-depth comprehension of traveling wave propagation. Consequently, equation is pivotal elucidating fundamental phenomena across applied sciences. A novel analytical technique, generalized Kudryashov method, presented address method combines fractional complex approach with modified enhance its effectiveness. We solution for elucidate how various parameters influence propagation new solutions. Furthermore, Figures 1 through 6 analyze impact $$\alpha$$ , $$\upbeta ,$$ $$b_{1}$$ $$k$$ on these Our results show that solitary solutions remain intact both case 2, regardless time orders $${ }\left( \upbeta \right)$$ . At end, manuscript discusses implications findings understanding phenomena, paving way further exploration applications studies.

Language: Английский

Hierarchical graph-based integration network for propaganda detection in textual news articles on social media DOI Creative Commons
Pir Noman Ahmad, J. Guo,

Nagwa M. AboElenein

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 13, 2025

During the Covid-19 pandemic, widespread use of social media platforms has facilitated dissemination information, fake news, and propaganda, serving as a vital source self-reported symptoms related to Covid-19. Existing graph-based models, such Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because challenges mining distinct word interactions storing nonconsecutive broad contextual data. In this study, we propose Hierarchical Graph-based Integration Network (H-GIN) designed detecting text within defined domain using multilabel classification. H-GIN is extracted build bi-layer graph inter-intra-channel, Residual-driven Enhancement (RDEP) Attention-driven Multichannel feature Fusing (ADMF) with suitable labels at two classification levels. First, RDEP procedures facilitate information between distant nodes. Second, by employing these guidelines, ADMF standardizes Tri-Channels 3-S (sequence, semantic, syntactic) layer, enabling effective through unrelated propagation news representations into classifier from existing ProText, Qprop, PTC datasets, thereby ensuring its availability public. The model demonstrated exceptional performance, achieving an impressive 82% accuracy surpassing current leading models. Notably, model's capacity identify previously unseen examples across diverse openness scenarios ProText dataset was particularly significant.

Language: Английский

Citations

2

An automatic teeth arrangement method based on an intelligent optimization algorithm and the Frenet–Serret formula DOI

Hong-an Li,

Man Liu

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 105, P. 107606 - 107606

Published: Feb. 5, 2025

Language: Английский

Citations

2

Predictive modeling of fractional plankton-assisted cholera propagation dynamics using Bayesian regularized deep cascaded exogenous neural networks DOI

A. V. Sultan,

Muhammad Junaid Ali Asif Raja,

Chuan‐Yu Chang

et al.

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 106819 - 106819

Published: Feb. 1, 2025

Language: Английский

Citations

2

Digital analysis of discrete fractional order worms transmission in wireless sensor systems: performance validation by artificial intelligence DOI
Aziz Khan, Thabet Abdeljawad,

Hisham Mohammad Alkhawar

et al.

Modeling Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 11(1)

Published: Dec. 23, 2024

Language: Английский

Citations

5

Autoregressive exogenous neural structures for synthetic datasets of olive disease control model with fractional Grünwald-Letnikov solver DOI
Nabeela Anwar, Muhammad Asif Zahoor Raja, Nabeela Anwar

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 187, P. 109707 - 109707

Published: Feb. 5, 2025

Language: Английский

Citations

0

Novel machine intelligent expedition with adaptive autoregressive exogenous neural structure for nonlinear multi-delay differential systems in computer virus propagation DOI
Nabeela Anwar,

Aqsa Saddiq,

Muhammad Asif Zahoor Raja

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 146, P. 110234 - 110234

Published: Feb. 20, 2025

Language: Английский

Citations

0

Dynamical analysis of hepatitis B virus through the stochastic and the deterministic model DOI
Nabeela Anwar,

Iftikhar Ahmad,

Hijab Javaid

et al.

Computer Methods in Biomechanics & Biomedical Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 17

Published: Feb. 28, 2025

In the current work, deterministic hepatitis B virus epidemic (DHBVE) model and stochastic (SHBVE) are two nonlinear mathematical models that serve as framework to illustrate predict dynamic behavior of B. We employ an approximation based on outcomes solve numerically. Euler-Maruyama method is employed investigate SHBVE model, whereas explicit Runge-Kutta exploited calculate solution DHBVE model. Finally, comparisons between models' frameworks presented.

Language: Английский

Citations

0

Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems DOI

Xujia Huang,

Fajie Wang, Benrong Zhang

et al.

Mathematics and Computers in Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

Language: Английский

Citations

0

Mathematical analysis of isothermal study of reverse roll coating using Micropolar fluid DOI Creative Commons
Saquib Ul Zaman, Azad Hussain,

Kaleem Ashraf

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 24, 2024

This article demonstrates a mathematical model and theoretical analysis of the Micropolar fluid in reverse roll coating process. It is important because micropolar fluids account for microstructure microrotation particles within fluid. These characteristics are significant accurately describing behavior complex such as polymer solutions, biological fluids, colloidal suspensions. First, we modeled flow equations using basic laws dynamics. The made modified low Reynolds number theory. simplified solved analytically. exact expression velocity pressure gradient obtained, while calculated numerically Simpson Rule. Graphical depictions carried out to comprehend impact newly emerged physical constraints. influence parameters on velocity, elaborated with help different graphs.

Language: Английский

Citations

3

Bayesian-regularized cascaded neural networks for fractional asymmetric carbon-thermal nutrient-plankton dynamics under global warming and climatic perturbations DOI

Muhammad Junaid Ali Asif Raja,

A. V. Sultan,

Chuan‐Yu Chang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 151, P. 110739 - 110739

Published: April 8, 2025

Language: Английский

Citations

0