Adaptive Network–Fuzzy Inferencing to Estimate Concrete Strength Using Mix Design
Publication: Journal of Materials in Civil Engineering
Volume 19, Issue 7
Abstract
Proportioning of concrete mixes is carried out in accordance with specified code information, specifications, and past experiences. Typically, concrete mix companies use different mix designs that are used to establish tried and tested datasets. Thus, a model can be developed based on existing datasets to estimate the concrete strength of a given mix proportioning and avoid costly tests and adjustments. Inherent uncertainties encountered in the model can be handled with fuzzy based methods, which are capable of incorporating information obtained from expert knowledge and datasets. In this paper, the use of adaptive neuro-fuzzy inferencing system is proposed to train a fuzzy model and estimate concrete strength. The efficiency of the proposed method is verified using actual concrete mix proportioning datasets reported in the literature, and the corresponding coefficient of determination range from 0.970–0.999. Further, sensitivity analysis is carried out to highlight the impact of different mix constituents on the estimate concrete strength.
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Information & Authors
Information
Published In
Journal of Materials in Civil Engineering
Volume 19 • Issue 7 • July 2007
Pages: 550 - 560
Copyright
© 2007 ASCE.
History
Received: Dec 16, 2005
Accepted: Nov 8, 2006
Published online: Jul 1, 2007
Published in print: Jul 2007
Notes
Note. Associate Editor: Kamran M. Nemati
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