Radial Basis Neural Network for Availability Analysis
2019 ◽
Vol 7
(2)
◽
pp. 103-110
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Keyword(s):
The appliance of radial basis neural network is demostrated in this paper. The method applies failure and repair rate signals to learn the hidden relationship presented into the input pattern. Statistics of availability of several years is considered and collected from the management of concern plant. This data is considered to train and calidate the radial basis neural network (RBNN). Subsequently validated RBNN is used to estimate the availability of concern plant. The main objective of using neural network approach is that it’s not require assumption, nor explicit coding of the problem and also not require the complete knowledge of interdependencies, only requirement is raw data of system functioning.
Keyword(s):
2001 ◽
Vol 39
(3)
◽
pp. 362-367
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Accurate radial basis function based neural network approach for analysis of photonic crystal fibers
2008 ◽
Vol 40
(11-12)
◽
pp. 891-905
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2008 ◽
Vol 71
(4)
◽
pp. 750-759
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Keyword(s):
2019 ◽
Vol 1373
◽
pp. 012034
Keyword(s):