Damage Condition Assessment of Expressway Asphalt Pavement Based on RBF Neural Network
2012 ◽
Vol 446-449
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pp. 2548-2553
Keyword(s):
In order to make the performance evaluation of highway asphalt pavement more scientific and reasonable, carrying out pavement maintenance management is more necessary. Taking advantage of excellent adaptability of neural network technology to deal with nonlinear mapping problem, a breakage condition evaluation model based on radial basis function (RBF) neural network is presented. This model considers four main affecting factors including pavement rut condition, crack condition, pit slot condition and repair condition. Certain number of sample data is chosen to train and simulate the RBF neural network model. The tests results, accordant with expectation, indicate that the model is qualified for practical engineering applications.
2012 ◽
Vol 446-449
◽
pp. 2548-2553
Keyword(s):
Keyword(s):
Keyword(s):
The Evaluation Model of the Hydropower Project Financing Risk Based on AHP-RS and RBF Neural Network
2011 ◽
Vol 474-476
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pp. 2243-2246
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2011 ◽
Vol 467-469
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pp. 1256-1261
2012 ◽
Vol 472-475
◽
pp. 1926-1931
2011 ◽
Vol 361-363
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pp. 1204-1210
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