Voronezh, Voronezh, Russian Federation
The article will explore the main theoretical aspects of the Poisson distribution and its application for event forecasting. We will examine the process of developing such models, algorithms for real-time data processing, and software tools that enable their implementation. Additionally, we will discuss examples of using these models in real-world conditions, as well as their advantages and limitations.
Poisson distribution, forecasting, data processing, algorithms, streaming data, models, statistical analysis
1. Krickiy O.L. Teoriya veroyatnostey i matematicheskaya statistika dlya tehnicheskih universitetov. I. Teoriya veroyatnostey: uchebnoe posobie / O.L. Krickiy, A.A. Mihal'chuk, A.Yu. Trifonov, M.L. Shinkeev; Tomskiy politehnicheskiy universitet. – Tomsk: Izd-vo Tomskogo politehnicheskogo universiteta, 2010. – 212 s
2. Zorich V. A. Matematicheskiy analiz. Chast' I. – Izd. 10-e, ispr. – M.: MCNMO, 2019. – xii+564 s. ISBN 978-5-4439-4029-8, 978-5-4439-4030-4 (ch. I).
3. Pechinkin A.V., Teskin O.I., Cvetkova G.M. i dr. Teoriya veroyatnostey : ucheb. dlya vuzov. – 3-e izd., isprav. – M.: Izd-vo MGTU im. N.E. Baumana, 2004. – 456 s.
4. Krishna Kumar, B. An M/G/1/1 queue with unreliable server and no waiting capacity / B. Krishna Kumar, D. Arivudainambi, A. Vijayakumar // Inf. Manage. Sci. – 2022. – Vol. 13. – P. 35–50.
5. Optimization analysis of an unreliable multi-server queue with a controllable repair policy / Wu C.-H., Lee W.-C., Ke J.-C., Liu T.-H. // Computers and Operations Research. – 2021. – № 49. – pp. 83-96.