Abstract
The mechanical properties of existing flexible pavements determine the remaining life of pavement and the moment when rehabilitation program should be implemented. The calculation of these properties can be very difficult, time consuming and non-reliable process. To determine the structural capacity of the pavement non-destructive testing equipment used. One of the most commonly used NDT techniques is falling weight deflectometer (FWD) test. Based on FWD measurements backcalculation process must be carried out in order to obtain the modulus of elasticity of pavement layers. This can be done by several methods, different in complexity and accuracy. Artificial neural networks can be successfully used for fast backcalculation process with training based on synthetic deflection basin obtained with linear elastic theory.
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Saric, A., Pozder, M. (2018). Artificial Neural Networks Application in the Backcalculation Process of Flexible Pavement Layers Elasticity Modulus. In: Hadžikadić, M., Avdaković, S. (eds) Advanced Technologies, Systems, and Applications II. IAT 2017. Lecture Notes in Networks and Systems, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71321-2_49
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DOI: https://doi.org/10.1007/978-3-319-71321-2_49
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