Abstract
In this paper a novel approach based on a machine learning algorithm (Hamming Clustering) is proposed to estimate the minimal cut and path sets, using the samples generated by a Monte Carlo simulation and any Evaluation Function. Two examples show the potential of the proposed approach.
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Rocco, C.M., Muselli, M. (2004). A Machine Learning Algorithm to Estimate Minimal Cut and Path Sets from a Monte Carlo Simulation. In: Spitzer, C., Schmocker, U., Dang, V.N. (eds) Probabilistic Safety Assessment and Management. Springer, London. https://doi.org/10.1007/978-0-85729-410-4_503
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DOI: https://doi.org/10.1007/978-0-85729-410-4_503
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1057-6
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