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Verification of application of ANN modelling in study of compressive behaviour of aluminium sponges

Stręk Anna M., Dudzik Marek, Kwiecień Arkadiusz, Wańczyk Krzysztof, Lipowska Barbara

Engineering Transactions

2019

Vol. 67, iss. 2

271--288

This article presents a preliminary neural network analysis of the compressive behaviour of aluminium open-cell sponges and answers the question of whether this phenomenon can be modelled using artificial intelligence. The research consisted of two phases: first – compression experiments, which in turn provided data for the second phase – the artificial neural network (ANN) analysis. A two-argument function was proposed and tested using the gathered experimental data with a two-layer feedforward network. The determination coefficient R 2 for linear correlation between targets and modelling outputs was chosen as the criterion for the assessment of the quality of modelling. The obtained values were R 2 > 0.96, which shows that neural networks hold the capacity to address the characterisation of the mechanical response of aluminium open-cell sponges in compression. Additionally, the mean absolute relative error (MARE) and the mean square error (MSE) were also determined.