Abstract
The aim of this thesis is to address capabilities in the prediction of compressive strength of concrete to affect quality control in construction. To comprehend this, a compressive strength predicting model using the principles of fuzzy logic set theory had been employed. The model put into use ‘fuzzy logic’ as a tool to predict the compressive strength of concrete on a given day. Data collected from previous researches and laboratory work had been put into use in the model construction and testing. The input variables of water/binder ratio, cement content, water content, and fly ash percentage and the output variable of 28-day cement compressive strength were fuzzified by the use of triangular membership functions and Gaussian membership functions which were deployed for the fuzzy subsets. The prediction of the 28-day cement strength data by the developed fuzzy model proved to be quite satisfactory. The training and testing of 4 different models were done. The Minimum average percentage error levels in the fuzzy model were seen to be as low as (3%) in the case of Model 3. A comparative study of the different models (all 3 Triangular and 1 Gaussian) had been done. The results indicated that the application of the fuzzy logic algorithm was quite satisfactory when a triangular membership function with decreased subset range was used. The outputs of the Triangular and Gaussian models were almost similar.
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