Prediction of modulus of elasticity and compressive strength of concrete specimens by means of artificial neural networks

Acta Scientiarum: Technology

José Fernando Moretti¹  Cesar Fabiano Fioriti¹  Jorge Luis Akasaki¹  José Luis Pinheiro Melges¹  Carlos Roberto Minussi¹  Mauro Mitsuuchi Tashima¹ 

[1] Universidade Estadual Paulista;

关键词: modulus of elasticity;    compressive strength;    concrete;    neural networks;    artificial intelligence;   

DOI  :  10.4025/actascitechnol.v38i1.27194

来源: DOAJ

【 摘 要 】

Currently, artificial neural networks are being widely used in various fields of science and engineering. Neural networks have the ability to learn through experience and existing examples, and then generate solutions and answers to new problems, involving even the effects of non-linearity in their variables. The aim of this study is to use a feed-forward neural network with back-propagation technique, to predict the values of compressive strength and modulus of elasticity, at 28 days, of different concrete mixtures prepared and tested in the laboratory. It demonstrates the ability of the neural networks to quantify the strength and the elastic modulus of concrete specimens prepared using different mix proportions.

【 授权许可】

Unknown