Journal
NEURAL COMPUTING & APPLICATIONS
Volume 19, Issue 4, Pages 507-513Publisher
SPRINGER
DOI: 10.1007/s00521-009-0292-9
Keywords
Heavyweight concrete; Baryte; Compressive strength; Artificial neural networks; Fuzzy logic; Computer simulation
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The compressive strength of heavyweight concrete which is produced using baryte aggregates has been predicted by artificial neural network (ANN) and fuzzy logic (FL) models. For these models 45 experimental results were used and trained. Cement rate, water rate, periods (7-28-90 days) and baryte (BaSO(4)) rate (%) were used as inputs and compressive strength (MPa) was used as output while developing both ANN and FL models. In the models, training and testing results have shown that ANN and FL systems have strong potential for predicting compressive strength of concretes containing baryte (BaSO(4)).
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