The Variables Reduction for Concrete Strength Prediction Model Using a Rough Sets Method

Abstract:

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Based on the test results of 448 sets of concrete mixtures (which have been divided into three groups), a concrete strength prediction model has been established using a stepwise regression method. The kinds and qualities of raw materials, which has a total comes to 17 factors, has been considered as the independent variables. It has been found that the forecast precision is not always improving along with the increase of independent variable number, so one or more factors may be "redundant" and should be reducted. A rough sets (RS) method has been adopted for the variable reduction, with different parameter combinations are tested. The results has shown that in each cases the forecast precision of the model are higher than the Bowromi formula’s. Some regularities for the parameters’ selections are existed, but not all the parameters can be given positively, so a trial process is still necessary.

Info:

Periodical:

Advanced Materials Research (Volumes 311-313)

Edited by:

Zhongning Guo

Pages:

1911-1915

DOI:

10.4028/www.scientific.net/AMR.311-313.1911

Citation:

B. Chen and X. J. Liu, "The Variables Reduction for Concrete Strength Prediction Model Using a Rough Sets Method", Advanced Materials Research, Vols. 311-313, pp. 1911-1915, 2011

Online since:

August 2011

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$35.00

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