A formal mathematical framework for modeling probabilistic hybrid systems [PDF]
Annals of Mathematics and Artificial Intelligence, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robert St-Aubin +2 more
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Combination system of slide variations of electric motors when using a probabilistic modelling approach of tractive effort distribution in multimotor drives of multidrive belt conveyors [PDF]
Научно-технический вестник Брянского государственного университета, 2019 The paper is aimed at specifying and summarizing system-wide and internal slide variations of electric motors in the structures of multimotor drives of multidrive belt conveyors.
Goncharov K.A.
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Convexity and Order in Probabilistic Call-by-Name FPC [PDF]
Logical Methods in Computer Science, 2020 Kegelspitzen are mathematical structures coined by Keimel and Plotkin, in order to encompass the structure of a convex set and the structure of a dcpo. In this paper, we ask ourselves what are Kegelspitzen the model of.
Mathys Rennela
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Deterministic-Probabilistic Approach to Predict Lightning-Caused Forest Fires in Mounting Areas
Forecasting, 2021 Forest fires from lightnings create a tense situation in various regions of states with forested areas. It is noted that in mountainous areas this is especially important in view of the geophysical processes of lightning activity. The aim of the study is
Nikolay Baranovskiy
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Mathematical Modelling and Analysis, 2019 The paper presents the solution methodology of a multi-objective probabilistic fractional programming problem, where the parameters of the right hand side constraints follow Cauchy distribution. The proposed mathematical model can not be solved directly.
Srikumar Acharya +2 more
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Probabilistic Learning and Psychological Similarity
Entropy, 2023 The notions of psychological similarity and probabilistic learning are key posits in cognitive, computational, and developmental psychology and in machine learning.
Nina Poth
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Probabilistic Formulations for Transferring Inferences from Mathematical Models to Physical Systems [PDF]
SIAM Journal on Scientific Computing, 2004 Summary: We outline a probabilistic framework for linking mathematical models to the physical systems that they represent, taking account of all sources of uncertainty including model and simulator imperfections. This framework is a necessary precondition for making probabilistic statements about the system on the basis of evaluations of computer ...
Goldstein, M, Rougier, JC
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Maximizing expected utility in the Arbitrage Pricing Model [PDF]
, 2017 We consider an infinite dimensional optimization problem motivated by mathematical economics. Within the celebrated "Arbitrage Pricing Model", we use probabilistic and functional analytic techniques to show the existence of optimal strategies for ...
Rasonyi, Miklos
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A model of distributed objectbased stochastic hybrid systems
Журнал Белорусского государственного университета: Математика, информатика, 2019 This article offers a mathematical model for distributed objectoriented stochastic hybrid systems (DOBSHS). DOBSHS are composite objects communicating with other objects through the exchange of messages through an asynchronous medium such as a network ...
Raman E. Sharykin +1 more
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THE INFLUENCE OF ADVERTISING ON THE DEMAND FORECASTING [PDF]
, 2012 This paper deals with the notion of approximate probabilistic bisimulation (APB) relation for discrete-time labeled Markov Chains (LMC). In order to provide a quantified upper bound on a metric over probabilistic realizations for LMC, we exploit the ...
Abate, Alessandro +2 more
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