Modeling Slump Flow of Concrete Using Genetic Programming

Abstract:

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The present study applied genetic programming (GP) to estimate the slump flow of high-performance concrete (HPC) using seven concrete ingredients. GP optimizes functions and their associated coefficients simultaneously and is suitable to automatically discover complex relationships between nonlinear systems. The results demonstrated that GP generates a more accurate formula and has lower estimating errors for predicting the slump flow of HPC than multiple linear regressions (MLRs).

Info:

Periodical:

Advanced Materials Research (Volumes 211-212)

Edited by:

Ran Chen

Pages:

374-378

DOI:

10.4028/www.scientific.net/AMR.211-212.374

Citation:

H. H. Hsu et al., "Modeling Slump Flow of Concrete Using Genetic Programming", Advanced Materials Research, Vols. 211-212, pp. 374-378, 2011

Online since:

February 2011

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Price:

$35.00

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