Results 181 to 190 of about 8,120 (265)

Global Results for Weakly Dispersive KP-II Equations on the Cylinder. [PDF]

Arch Ration Mech Anal
Herr S, Schippa R, Tzvetkov N.
europepmc   +1 more source

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

AIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho, Akshay Kudva, Parth Shah, Dongheon Lee, Joseph Sang‐Il Kwon   +4 more
wiley   +1 more source

Dynamical analysis and soliton solutions to (3+1)-dimensional extended quantum nonlinear Zakharov-Kuznetsov equation. [PDF]

Sci Rep
Fatima M, Abbas M, Higazy M, Anwar MN, Yousaf MZ, Birhanu A, Hamed YS.   +6 more
europepmc   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

Advanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al‐Fahdi, Lingyu Kong, Victor Fung, Ming Hu   +5 more
wiley   +1 more source

Simultaneous Numerical Determination of Two Time-dependent Coefficients in Second Order Parabolic Equation With Nonlocal Initial and Boundary Conditions. [PDF]

F1000Res
A J Al-Shatrah M, Sabah Hussein M.
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Compatibility of the evolution equation for heat flux in dual-phase-lag and three-phase-lag with the principles of thermodynamics. [PDF]

Sci Rep
Fawzy A, Mahmoud W, Rawy EK, Ghaleb AF.
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Optical solutions to time-fractional improved (2+1)-dimensional nonlinear Schrödinger equation in optical fibers. [PDF]

Sci Rep
Murad MAS, Tedjani AH, Li Z, Hussain E.
europepmc   +1 more source