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This article is cited in 5 scientific papers (total in 5 papers)
Neural Network Approximation of Characteristics of Multi-Channel Non-Markovian Queuing Systems
A. D. Khomonenkoa, E. L. Yakovlevb a Petersburg State Transport University
b Mozhaisky Military Space Academy
Abstract:
It is proposed to use a neural network to calculate an approximation of the probabilistic-time characteristics of multichannel queuing systems (QS) with a "warm-up" and the unlimited capacity of the queue. From the results of numerical experiments, we observe a significant reduction in the complexity of computing probabilistic-time characteristics of the multi-channel QS with "warm-up" with minor errors of calculation of characteristics, compared with the numerical iterative algorithms. The advisability of the use of Bayesian regularization method for training a neural network and the best number of neurons are shown.
Keywords:
multichannel queuing systems; neural networks; approximation; service systems with "warm-up".
Citation:
A. D. Khomonenko, E. L. Yakovlev, “Neural Network Approximation of Characteristics of Multi-Channel Non-Markovian Queuing Systems”, Tr. SPIIRAN, 41 (2015), 81–93
Linking options:
https://www.mathnet.ru/eng/trspy816 https://www.mathnet.ru/eng/trspy/v41/p81
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Abstract page: | 229 | Full-text PDF : | 158 |
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