DocumentCode :
3501606
Title :
Compression Strength Prediction of Mixtures Concrete with Scrap Tire with Neural Network Approach
Author :
Acevedo-Davila, J.L. ; Torres-Trevio, L.M.
Author_Institution :
Corporacion Mexicana de Investig. en Mater.
fYear :
2008
fDate :
27-31 Oct. 2008
Firstpage :
358
Lastpage :
362
Abstract :
The compressive strength of mixtures made with scrap tire id presented. In this study, neural network modeling was applied for predicting compressive strength of mixtures containing variable size of tire scrap. This modeling allows avoiding a large number of trial mixtures tests and provides a new alternative for designing new constructive components at lower costs. Results shown that neural model showed an excellent performance and accurate and highly reproducible predictions.
Keywords :
compressive strength; mechanical engineering computing; neural nets; recycling; tyres; compression strength prediction; compressive strength; mixtures concrete; neural network approach; scrap tire; Artificial neural networks; Concrete; Costs; Equations; Neural networks; Neurons; Predictive models; Production; Rubber products; Tires; Compression Strength Prediction; Mixture concrete design; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, 2008. MICAI '08. Seventh Mexican International Conference on
Conference_Location :
Atizapan de Zaragoza
Print_ISBN :
978-0-7695-3441-1
Type :
conf
DOI :
10.1109/MICAI.2008.43
Filename :
4682488
Link To Document :
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