Using a Machine Learning Approach for Analysis of Polling Systems with Correlated Arrivals-Reference-Cited by-同舟云学术

Using a Machine Learning Approach for Analysis of Polling Systems with Correlated Arrivals

Published:2021 Issue: Volume: Page:336-345
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Vishnevsky Vladimir^ORCID,Semenova Olga^ORCID,Bui D. T.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-92507-9_27

Reference13 articles.

1. Vishnevsky, V., Semenova, O.: Polling systems and their application to telecommunication networks. Mathematics 9(2), 117 (2021)

2. Boon, M.A.A., van der Mei, R.D., Winands, E.M.M.: Applications of polling systems. Surv. Oper. Res. Manage. Sci. 16(2), 67–82 (2011)

3. Vishnevsky, V.M., Semenova, O.V., Bui, D.T.: Software complex for evaluating the characteristics of stochastic polling systems: Certificate of state registration of a computer program No. 2019614554 of the Russian Federation; Registered 04 April 2019

4. Cybenko, J.: Approximations by superpositions of a sigmoidal function. Math. Control Signals Syst. 2(4), 303–314 (1989)

5. Sivakami Sundari, M., Palaniammal, S.: Simulation of $$M/M/1$$ queuing system using ANN. Malaya J. Matematik 1, 279–294 (2015)

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