Results 151 to 160 of about 4,822 (250)

Multi‐Goal‐Oriented Anisotropic Error Control and Mesh Adaptivity for Time‐Dependent Convection‐Dominated Problems

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT In this work, we present an anisotropic multi‐goal error control based on the dual weighted residual (DWR) method for time‐dependent convection–diffusion–reaction (CDR) equations. Motivated by former work, we combine multiple goals to single error functionals with weights chosen as algorithmic parameters.
Markus Bause, Marius Paul Bruchhäuser, Bernhard Endtmayer, Nils Margenberg, Ioannis Toulopoulos, Thomas Wick   +5 more
wiley   +1 more source

A neural network model for managing renewable resources with population growth. [PDF]

Sci Rep
Ahmad S, Ahmad I, Alluhaidan AS, ElAffendi MA.   +3 more
europepmc   +1 more source

Discontinuous Galerkin Trefftz Methods for Model Reduction of Wave Phenomena

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT The space–time discontinuous Galerkin (dG)‐Trefftz is known to be a highly efficient numerical scheme for solving linear hyperbolic problems. We investigate to what extent such a dG‐Trefftz method can be used as a basis for a model reduction method for a traveling wave problem using the wave speed as a parameter.
Tobias Born, Karsten Urban
wiley   +1 more source

Singularity in nonlinear systems: differential inclusion model for the standard and transformed fractional pantograph equation. [PDF]

Sci Rep
Mobayen S, Ghaderi M, Shabibi M, Parvaneh Masiha H, Rezapour S.   +4 more
europepmc   +1 more source

Recursive Feasibility of Nonlinear Stochastic Model Predictive Control With Gaussian Process Dynamics

International Journal of Robust and Nonlinear Control, Volume 36, Issue 9, Page 4957-4970, June 2026.
ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf, Andreas Völz, Knut Graichen   +2 more
wiley   +1 more source

Nonlinear fractional stochastic delay modeling and computational analysis of herpes simplex virus type II dynamics. [PDF]

Sci Rep
Raza A, Alsulami M, Lampart M, Shafique U.   +3 more
europepmc   +1 more source

Functions with prescribed Lipschitz condition [PDF]

Proceedings of the American Mathematical Society, 1951
openaire   +1 more source

A Deep Learning‐Enhanced Ensemble Smoother for Non‐Gaussian Hydrological Data Assimilation Without Relying on Innovation Vectors

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.
Abstract Data assimilation (DA) plays a critical role in reducing simulation uncertainty in hydrological systems by leveraging available observations to estimate model states and/or parameters. Among DA methods, the ensemble smoother (ES) has emerged as an attractive option for parameter estimation due to its computational efficiency and ...
Jiangjiang Zhang, Junliang Jin, Lei Yao, Kun Zhou, Jianyun Zhang   +4 more
wiley   +1 more source

Beyond diagonal noise: A better predator-prey modeling framework with cross-covariance. [PDF]

PLoS One
Yu J, Wang LS.
europepmc   +1 more source

From gateway to value ladder—The curious case of online mutual aid in China

Journal of Risk and Insurance, Volume 93, Issue 2, Page 349-387, June 2026.
Abstract This study examines how InsurTech‐enabled information provision, specifically the disclosure of claimant information previously unavailable in conventional insurance, influences individuals' insurance uptake. We leverage Mutual Aid (MA) platforms as a natural context to examine how socially framed loss information, peer influence, and salience
Ze Chen, Runhuan Feng, Miao Guo, Tianyang Wang   +3 more
wiley   +1 more source