Asymptotic Relations in Applied Models of Inhomogeneous Poisson Point Flows

Gurami Tsitsiashvili () and Marina Osipova
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Gurami Tsitsiashvili: Institute for Applied Mathematics, Far Eastern Branch of Russian Academy of Sciences, 690041 Vladivostok, Russia
Marina Osipova: Institute for Applied Mathematics, Far Eastern Branch of Russian Academy of Sciences, 690041 Vladivostok, Russia

Mathematics, 2023, vol. 11, issue 8, 1-10

Abstract: A model of a particle flow forming a copy of some image and the distance between the copy and the image are estimated using a special probability metric. The ability of the flow of balls to cover the surface, when grinding the balls, was investigated using formulas of stochastic geometry. Reconstruction of characteristics of an inhomogeneous Poisson flow by inaccurate observations is analysed using the Poisson flow point colouring theorem. The dependence of the Poisson parameter of the distribution of the number of customers in a queuing system with an infinite number of servers and a deterministic service time on the peak load created by an inhomogeneous input Poisson flow is estimated. All these models consist of an inhomogeneous Poisson flow of points and marks glued to each point of the flow and are characterised by their mass, area, volume, observability (or non-observability), and service time. The presence of an asymptotic power–law relationship between model objective functions and parameters of mark crushing is established. These results may be applied in nanotechnology, powder metallurgy, ecology, and consumer services in the implementation of the “Smart City” program. The proposed approach is phenomenological in nature and is justified by the results of real observations and experiments.

Keywords: Poisson point flow; stochastic geometry; safety margin; linear regression estimate; plan of experiment; prediction algorithms; polynomial (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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