Open AccessUSING APPLICATION OF AN ARTIFICIAL NEURAL NETWORK SYSTEM TO BACKCALCULATE PAVEMENT ELASTIC MODULUS
Author(s) -
M. M. M. Elshamy,
A. N. Tiraturyan
Publication year - 2020
Publication title -
russian journal of building construction and architecture
Language(s) - English
Resource type - Journals
ISSN - 2542-0526
DOI - 10.36622/vstu.2020.2.46.006
Subject(s) - artificial neural network , computer science , set (abstract data type) , elastic modulus , backpropagation , structural engineering , moduli , artificial intelligence , algorithm , engineering , materials science , composite material , physics , quantum mechanics , programming language
Statement of the problem. The article is devoted to the use of artificial neural networks in solving the problems of processing the results of instrumental recording of bowls of flexible pavement deflections using FWD shock loading settings. Results. The analysis was carried out, the shortcomings of the existing processing methods were noted, in particular the “backcalculation” method, which consists of a long calculation time, and the instability of the results obtained. The structure of the artificial neural network was built to determine the elastic moduli of the pavement layers. Training of an artificial neural network was carried out using the method of back propagation of error. Conclusions. The developed neural network has shown good results in training on the test data set, as well as high accuracy of prediction of the elastic moduli of the pavement.