Copertina

Physics Informed Optimal Homotopy Analysis Method (PI-OHAM): A Hybrid Analytical Computational Framework for Solving nonlinear Differential Equations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Uddin, Ziya
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computational Engineering, Finance, and Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Exploring Physics-Informed Neural Networks: From Fundamentals to Applications in Complex Systems
di: Ganga, Sai, et al.
Pubblicazione: (2024)

Solving Differential Equations with Constrained Learning
di: Moro, Viggo, et al.
Pubblicazione: (2024)

Bridging Computational Fluid Dynamics Algorithm and Physics-Informed Learning: SIMPLE-PINN for Incompressible Navier-Stokes Equations
di: Wei, Chang, et al.
Pubblicazione: (2026)

Physics-Informed Neural Networks for Solving Contact Problems in Three Dimensions
di: Sahin, Tarik, et al.
Pubblicazione: (2024)

Physics-Informed Holomorphic Neural Networks (PIHNNs): Solving Linear Elasticity Problems
di: Calafà, Matteo, et al.
Pubblicazione: (2024)

Physics Informed Neural Network using Finite Difference Method
di: Lim, Kart Leong, et al.
Pubblicazione: (2026)

Physics-Enforced Neural Ordinary Differential Equation for Chemical Kinetics Optimization in Reaction-Diffusion Systems
di: Cai, Feixue, et al.
Pubblicazione: (2026)

Solving Stochastic Differential Equations with Jump-Diffusion Efficiently: Applications to FPT Problems in Credit Risk
di: Zhang, Di, et al.
Pubblicazione: (2007)

Physics-Informed Machine Learning for Battery Degradation Diagnostics: A Comparison of State-of-the-Art Methods
di: Navidi, Sina, et al.
Pubblicazione: (2024)

Adaptive Finite State Projection with Quantile-Based Pruning for Solving the Chemical Master Equation
di: Dendukuri, Aditya, et al.
Pubblicazione: (2025)

Enforced Interface Constraints for Domain Decomposition Method of Discrete Physics-Informed Neural Networks
di: Yin, Jichao, et al.
Pubblicazione: (2025)

A Dual Physics-Informed Kolmogorov-Arnold Neural Network Framework for Continuum Topology Optimization
di: Zhang, Junyuan, et al.
Pubblicazione: (2026)

Universal Differential Equations as a Common Modeling Language for Neuroscience
di: ElGazzar, Ahmed, et al.
Pubblicazione: (2024)

Optimal Box Contraction for Solving Linear Systems via Simulated and Quantum Annealing
di: Suresh, Sanjay, et al.
Pubblicazione: (2024)

Provably Efficient Quantum Algorithms for Solving Nonlinear Differential Equations Using Multiple Bosonic Modes Coupled with Qubits
di: Gan, Yu, et al.
Pubblicazione: (2025)

A Physics-Informed Neural Network Framework for Simulating Creep Buckling in Growing Viscoelastic Biological Tissues
di: Lin, Zhongya, et al.
Pubblicazione: (2025)

Towards a Hybrid Digital Twin: Physics-Informed Neural Networks as Surrogate Model of a Reinforced Concrete Beam
di: Sahin, Tarik, et al.
Pubblicazione: (2024)

An Agentic AI Workflow to Simplify Parameter Estimation of Complex Differential Equation Systems
di: Bhatnagar, Saakaar
Pubblicazione: (2025)

GeoMCP: A Trustworthy Framework for AI-Assisted Analytical Geotechnical Engineering
di: Bekele, Yared W.
Pubblicazione: (2026)

Investigation on the Shooting Method Ability to Solve Different Mooring Lines Boundary Condition Types
di: Surmont, Florian, et al.
Pubblicazione: (2024)

Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems
di: Yuan, Biao, et al.
Pubblicazione: (2024)

Solving Electromagnetic Scattering Problems by Isogeometric Analysis with Deep Operator Learning
di: Backmeyer, Merle, et al.
Pubblicazione: (2024)

TOFLUX: A Differentiable Topology Optimization Framework for Multiphysics Fluidic Problems
di: Padhy, Rahul Kumar, et al.
Pubblicazione: (2025)

Perturbative Analytical Framework for Thermal Wave Diffusion in Non-linear Building Envelopes
di: Guigot, Corentin
Pubblicazione: (2026)

PRIMAD-LID: A Developed Framework for Computational Reproducibility
di: Aloqalaa, Meznah, et al.
Pubblicazione: (2026)

Deep Feynman-Kac Methods for High-dimensional Semilinear Parabolic Equations: Revisit
di: Zheng, Xiaotao, et al.
Pubblicazione: (2025)

Isogeometric Shape Optimization of Multi-Tapered Coaxial Baluns Simulated by an Integral Equation Method
di: Balouchev, Boian, et al.
Pubblicazione: (2024)

A Monolithic Computational Homogenization Framework for Nearly Incompressible Magnetoelastic Composites
di: Spencer, L. River, et al.
Pubblicazione: (2026)

Solving strategies for data-driven one-dimensional elasticity exhibiting nonlinear strains
di: Nguyen, Thi-Hoa, et al.
Pubblicazione: (2025)

PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
di: Zhao, Zhiyuan, et al.
Pubblicazione: (2023)

On a High-Frequency Analysis of Some Relevant Integral Equations in Electromagnetics
di: Giunzioni, V., et al.
Pubblicazione: (2024)

Exascale Implicit Kinetic Plasma Simulations on El~Capitan for Solving the Micro-Macro Coupling in Magnetospheric Physics
di: Markidis, Stefano, et al.
Pubblicazione: (2025)

A Taxonomy of Numerical Differentiation Methods
di: Komarov, Pavel, et al.
Pubblicazione: (2025)

Physics-Informed Video Diffusion For Shallow Water Equations
di: Bai, Yang, et al.
Pubblicazione: (2026)

A Concept for Autonomous Problem-Solving in Intralogistics Scenarios
di: Sigel, Johannes, et al.
Pubblicazione: (2025)

Quantum Homotopy Algorithm for Solving Nonlinear PDEs and Flow Problems
di: Bharadwaj, Sachin S., et al.
Pubblicazione: (2025)

Quantum Optimization for Electromagnetics: Physics-Informed QAOA for Reconfigurable Intelligent Surfaces
di: Pasquale, Marco, et al.
Pubblicazione: (2026)

Physics-Informed Transformer for Real-Time High-Fidelity Topology Optimization
di: Lutheran, Aaron, et al.
Pubblicazione: (2026)

I-FENN for thermoelasticity based on physics-informed temporal convolutional network (PI-TCN)
di: Abueidda, Diab W., et al.
Pubblicazione: (2023)

A Knowledge-Inspired Hierarchical Physics-Informed Neural Network for Pipeline Hydraulic Transient Simulation
di: Du, Jian, et al.
Pubblicazione: (2024)