Results 51 to 60 of about 2,971,628 (227)
IEEE AccessAiming at the objective uncertainty, subjective uncertainty, and extreme events may be in a dynamic system simultaneously. This paper focuses on the differential game problem of a linear quadratic jump uncertain stochastic system. The system is described
Lu Yang +3 more
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Closed-Loop Solvability of Stochastic Linear-Quadratic Optimal Control Problems with Poisson Jumps
Mathematics, 2022 The stochastic linear–quadratic optimal control problem with Poisson jumps is addressed in this paper. The coefficients in the state equation and the weighting matrices in the cost functional are all deterministic but are allowed to be indefinite.
Zixuan Li, Jingtao Shi
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Журнал Белорусского государственного университета: Математика, информатика, 2018 The Cauchy problem for stochastic differential system with measures is considered in the paper. Finite-difference with averaging system of stochastic differential equations with correspondence to Cauchy problem is investigated.
Artsiom Y. Rusetski
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Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Numerical methods for stochastic differential equations [PDF]
Physical Review E, 2004 Stochastic differential equations (sdes) play an important role in physics but existing numerical methods for solving such equations are of low accuracy and poor stability. A general strategy for developing accurate and efficient schemes for solving stochastic equations in outlined here.
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Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
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AxiomsThis paper continues a series of papers by the author devoted to unsolved problems in the theory of stability and optimal control for stochastic systems.
Leonid Shaikhet
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The Optimal Discretization of Stochastic Differential Equations
Journal of Complexity, 2001 The paper studies discrete time pathwise approximations of stochastic differential equations. An adaptive discretization is introduced that reflects local properties of the simulated trajectory. The corresponding error is shown to converge to zero in average with a certain rate.
Norbert Hofmann +2 more
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Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source