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Transport equation driven by a stochastic measure
Modern Stochastics: Theory and Applications, 2023 The stochastic transport equation is considered where the randomness is given by a symmetric integral with respect to a stochastic measure. For a stochastic measure, only σ-additivity in probability and continuity of paths is assumed.
Vadym Radchenko
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Asymptotic properties of the parabolic equation driven by stochastic measure
Modern Stochastics: Theory and Applications, 2022 A stochastic parabolic equation on $[0,T]\times \mathbb{R}$ driven by a general stochastic measure, for which we assume only σ-additivity in probability, is considered. The asymptotic behavior of its solution as $t\to \infty $ is studied.
Boris Manikin
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The Burgers equation driven by a stochastic measure
Modern Stochastics: Theory and Applications, 2023 The class of one-dimensional equations driven by a stochastic measure μ is studied. For μ only σ-additivity in probability is assumed. This class of equations includes the Burgers equation and the heat equation.
Vadym Radchenko
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Averaging principle for the one-dimensional parabolic equation driven by stochastic measure
Modern Stochastics: Theory and Applications, 2022 A stochastic parabolic equation on $[0,T]\times \mathbb{R}$ driven by a general stochastic measure is considered. The averaging principle for the equation is established. The convergence rate is compared with other results on related topics.
Boris Manikin
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Coarse-Graining of Observables
Quantum Reports, 2022 We first define the coarse-graining of probability measures in terms of stochastic kernels. We define when a probability measure is part of another probability measure and say that two probability measures coexist if they are both parts of a single ...
Stan Gudder
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A maximum flow network interdiction model in fuzzy stochastic hybrid uncertainty environments [PDF]
Yugoslav Journal of Operations Research, 2023 Uncertainty is an inherent characteristic of a decision-making process. Occasionally, historical data may be insufficient to accurately estimate the probability distribution suitable for an unknown variable.
Bavandi Salim, Bigdeli Hamid
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Weighted survival functional entropy and its properties
Open Physics, 2023 The weighted generalized cumulative residual entropy is a recently defined dispersion measure. This article introduces a new uncertainty measure as a generalization of the weighted generalized cumulative residual entropy, called it the weighted ...
Alomani Ghadah, Kayid Mohamed
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On relation between one multiple and a corresponding one-dimensional integral with applications [PDF]
Yugoslav Journal of Operations Research, 2018 For a given finite positive measure on an interval I ⊆ R, a multiple stochastic integral of a Volterra kernel with respect to a product of a corresponding Gaussian orthogonal stochastic measure is introduced.
Bajić Tatjana
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Multi-Agent Based Stochastic Dynamical Model to Measure Community Resilience
Journal of Social Computing, 2022 Emergency services and utilities need appropriate planning tools to analyze and improve infrastructure and community resilience to disasters. Recognized as a key metric of community resilience is the social well-being of a community during a disaster ...
Jaber Valinejad +2 more
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Majorization and semidoubly stochastic operators on L 1 ( X ) $L^{1}(X)$
Journal of Inequalities and Applications, 2023 This paper is devoted to a study of majorization based on semidoubly stochastic operators (denoted by S D ( L 1 ) $S\mathcal{D}(L^{1})$ ) on L 1 ( X ) $L^{1}(X)$ when X is a σ-finite measure space.
Seyed Mahmoud Manjegani, Shirin Moein
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