Abstract
This paper describes an approach of combining Monte Carlo simulation and neural nets. The approach is applied to model transport systems, with the accurate but computationally expensive Monte Carlo simulation used to train a neural net. Once trained the neural net can efficiently provide functional analysis and reliability predictions. No restriction on the system structure and on any kind of distribution is the main advantage of the proposed approach. The paper presents exemplar decision problem solved by proposed approach.
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Walkowiak, T., Mazurkiewicz, J. (2008). Neural Network Device for Reliability and Functional Analysis of Discrete Transport System. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_18
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DOI: https://doi.org/10.1007/978-3-540-69731-2_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
Online ISBN: 978-3-540-69731-2
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