Results 121 to 130 of about 889,087 (322)
Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi +2 more
wiley +1 more source
AI in chemical engineering: From promise to practice
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Boundary value problems for systems of non-degenerate difference-algebraic equations
The study of differential-algebraic boundary value problems was initiated in the works of K. Weierstrass, N.N. Luzin and F.R. Gantmacher. Systematic study of differential-algebraic boundary value problems is devoted to the work of S.
Sergey Chuiko +2 more
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Rosenbrock methods for Differential Algebraic Equations
This paper deals with the numerical solution of differential algebraic equations (DAE) of index one. It begins with the development of a general theory on the Taylor expansion for the exact solutions of these problems, which extends the well known theory of Butcher for first order ordinary differential equations to DAE's of index one. As an application,
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This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Aspects of derivative causality in bond-graph models
The bond-graph method used in the analysis of system dynamics problems leads to a system containing a number of differential equations equal to the number of energy storing elements in integral causality and a number of algebraic equations equal to the ...
Ibănescu Radu, Ibănescu Mihaela
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In this paper, we present the Taylor polynomial solutions of system of higher order linear integro-differential Volterra-Fredholm equations (IDVFE). This method transforms IDVFE into the matrix equations which correspond to a system of linear algebraic ...
Yousef Jafarzadeh, Bagher Keramati
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Differential/Algebraic Equations As Stiff Ordinary Differential Equations
To a system of differential algebraic equations: \[ \text{(DAE)}\quad y'(t)=f(t,y(t),z(t),0),\quad g(t,y(t),z(t),0)=0, \] a system of singularly perturbed ordinary differential equations: \[ \text{(ODE)}\quad y_ \varepsilon'(t)=f(t,y_ \varepsilon(t),z_ \varepsilon(t),\varepsilon), \varepsilon z_ \varepsilon'(t)=g(t,y_ \varepsilon(t),z_ \varepsilon(t ...
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Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source

