Results 101 to 110 of about 6,299 (269)
Food Tastes in the United States: Convergence or Divergence?
Agribusiness, EarlyView.ABSTRACT This study investigates how food consumption tastes have changed in recent decades across the United States. Using NielsenIQ data for over 77 million transactions, there is evidence of divergence in food tastes across regions from 2007 to 2016 and across households of different income, education, and race/ethnicity groups.
Michael DeDad
wiley +1 more source
Flows of singular vector fields and applications to fluid and kinetic equations [PDF]
, 2015 Several physical phenomena arising in fluid dynamics and kinetic equations can be modeled by nonlinear transport PDE. Such quantities are the vorticity of a fluid, or the density of a collection of particles advected by a velocity field which is highly ...
Bohun, Anna
core +1 more source
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 +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas +4 more
wiley +1 more source
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
Numerical Analysis of Higher Order Discontinuous Galerkin Finite Element Methods
, 2008 After the introduction in Section 1 this lecture starts off with recalling well-known results from the numerical analysis of the continuous finite element methods.
Hartmann, Ralf
core
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
MathematicsWhile recent advances have successfully integrated neural networks with physical models to derive numerical solutions, there remains a compelling need to obtain exact analytical solutions.
Jan Muhammad +3 more
doaj +1 more source
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Advanced Intelligent Discovery, EarlyView.Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Fourth order abstract evolution equations
, 1992 Higher order evolution equations in Hilbert space may be sometimes better studied by ad hoc methods, rather than reducing them to first order systems. We illustrate this by solving the Cauchy problem for equations, which are variations on the theme of ...
PANIZZI, Stefano +3 more
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