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Title: Backcalculation of pavement layer parameters using Artificial Neural Networks
Authors: Saltan, Mehmet
Terzi, Serdal
Issue Date: Feb-2004
Publisher: CSIR
Abstract: In this paper, a new formulation based on Artificial Neural Networks (ANN) is presented for backcalculation of pavement layer moduli. In structural analysis of flexible pavements, the procedures as Layered Elastic Theory, Equivalent Layer Thickness (ELT), and Finite Elements Method (FEM) generally have complex formulations and give approximate results. Therefore, it is extremely difficult to perform realistic analysis for flexible pavements, especially in view of modelling the material properties of layers in these methods. Setting the finite element mesh and iteration procedure of backcalculation takes rather long time. The proposed ANN procedure requires significantly less computation time. ELT method is used for simplicity. It is impossible or very hard to model the visco-elastic and non-linear behaviour of layer materials in layered elastic theory. The use of ANN is proliferating with high rate in simulation. The ability of ANN is to learn complex nonlinear relationships. A new formulation using ANN is presented here.
Page(s): 38-42
ISSN: 0975-1017 (Online); 0971-4588 (Print)
Appears in Collections:IJEMS Vol.11(1) [February 2004]

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