Adaptive network-fuzzy inferencing to estimate concrete strength using mix design

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TypeTechnical Report
Series titleJournal of Materials in Civil Engineering; Volume 19
Physical description560 p.
Subjectfuzzy sets, compressive strength, concrete, mixing, strength; Concrete
AbstractTypically, concrete mix companies use different mix designs 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 an adaptive neuro-fuzzy inferencing system (ANFIS) 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. Further, sensitivity analysis is carried out to highlight the impact of different mix constituents on the estimated concrete strength.
Publication date
PublisherNational Research Council Canada
AffiliationNRC Institute for Research in Construction; National Research Council Canada
Peer reviewedNo
NRC number49681
NPARC number20378424
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Record identifier9ce54a2e-6d81-4a9c-a34f-4da10671d0a0
Record created2012-07-24
Record modified2017-05-23
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