Prediction of Resilient Modulus for Hot Mix Asphalt Based on Artificial Neural Network

Abstract:

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Resilient modulus of material is an important parameter for pavement structure design and analysis. However it is very tedious to get this parameter for hot mixture asphalt in laboratory. Moreover it takes long time to do experiments. In this paper, artificial neural network (ANN) is applied to predict to resilient modulus for hot mixture asphalt. A neural network model is constructed and trained plenty of times with selected test data until precision meets requirement. Then the model is used to predict resilient modulus for hot mix asphalt. Result of contrast prediction with test data shows that forecast precision is high. This provides a new method to predict resilient modulus for hot mixture asphalt.

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Periodical:

Edited by:

Jerry Tian

Pages:

18-23

DOI:

10.4028/www.scientific.net/AMR.304.18

Citation:

C. H. Hu "Prediction of Resilient Modulus for Hot Mix Asphalt Based on Artificial Neural Network", Advanced Materials Research, Vol. 304, pp. 18-23, 2011

Online since:

July 2011

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Price:

$35.00

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