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Ingeniería e Investigación

versão impressa ISSN 0120-5609

Resumo

LIZARAZO MARRIAGA, Juan Manuel  e  GOMEZ CORTES, José Gabriel. Developing an artificial neural network model for predicting concrete’s compression strength and electrical resistivity. Ing. Investig. [online]. 2007, vol.27, n.1, pp.11-18. ISSN 0120-5609.

The present study was conducted for predicting the compressive strength of concrete based on unit weight ultrasonic and pulse velocity (UPV) for 41 different concrete mixtures. This research emerged from the need for a rapid test for predicting concrete’s compressive strength. The research was also conducted for predicting concrete’s electrical resistivity based on unit weight ultrasonic, pulse velocity (UPV) and compressive strength with the same mixes. The prediction was made using simple regression analysis and artificial neural networks. The results revealed that artificial neural networks can be used for effectively predicting compressive strength and electrical resistivity.

Palavras-chave : neural network; concrete strength; concrete resistivity; concrete ultrasonic pulse velocity.

        · resumo em Espanhol     · texto em Espanhol     · Espanhol ( pdf )

 

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