The reliability of communication networks is assessed by employing two machine learning algorithms, Support Vector Machines (SVM) and Hamming Clustering (HC), acting on a subset of possible system con- ¯gurations, generated by a Monte Carlo simulation and an appropriate Evaluation Function. The experiments performed with two di®erent re- liability measures show that both methods yield excellent predictions, though the performances of models generated by HC are signi¯cantly better than those of SVM.
Assessing the reliability of communication networks through machine learning techniques
M Muselli
2005
Abstract
The reliability of communication networks is assessed by employing two machine learning algorithms, Support Vector Machines (SVM) and Hamming Clustering (HC), acting on a subset of possible system con- ¯gurations, generated by a Monte Carlo simulation and an appropriate Evaluation Function. The experiments performed with two di®erent re- liability measures show that both methods yield excellent predictions, though the performances of models generated by HC are signi¯cantly better than those of SVM.File in questo prodotto:
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