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Adaptive statistical algorithms in network reliability analysis
The paper is concerned with introducing novel algorithms, such as adaptive approximation and deterministic radial basis function (RBF) method, for calculating the average loss (AL). Different approximators are trained to approximate the loss function and, after a short learning period, AL can be eva...
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Published in: | Performance evaluation 2002-06, Vol.48 (1), p.225-236 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The paper is concerned with introducing novel algorithms, such as adaptive approximation and deterministic radial basis function (RBF) method, for calculating the average loss (AL). Different approximators are trained to approximate the loss function and, after a short learning period, AL can be evaluated analytically with fast calculations. An improvement of the Li–Silvester (LS) method is also presented which yields a sharper lower bound on AL. The efficiency of the new methods are proven by theoretical analysis as well as demonstrated by excessive simulations. |
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ISSN: | 0166-5316 1872-745X |
DOI: | 10.1016/S0166-5316(02)00038-X |