A COMPARISON OF TWO MAJOR APPROACHES USED FOR CONCRETE STRENGTH PREDICTION FOR DIFFERENT CONCRETE TYPES

Author(s): Seda Yesilmen (1), Sinan Kefeli (1)
Paper category: Proceedings
Book title: SynerCrete’18 International Conference on Interdisciplinary Approaches for Cement-based Materials and Structural Concrete
Editor(s): Miguel Azenha, Dirk Schlicke, Farid Benboudjema, Agnieszka Jędrzejewska
ISBN: 978-2-35158-202-2
e-ISBN: 978-2-35158-203-9
Publisher: RILEM Publications SARL
Publication year: 2018
Pages: 901-906
Total Pages: 6
Language : English

Abstract: Predicting concrete strength has been a popular topic for the last decade and several methods were proposed by researchers each claiming to increase accuracy of predictions. Two methods were selected namely linear regression, and artificial neural networks and their predictive performances were compared using data for different concrete types. Data for high performance concrete (HPC), self-compacting concrete (SCC) and ordinary concrete (OC) were implemented in selected prediction models.

Online publication : 2018
Publication type : full_text
Public price (Euros) : 0.00