Comparison of response surface methodology and hybrid-training approach of artificial neural network in modelling the properties of concrete containing steel fibre extracted from waste tyres

Comparison of response surface methodology and hybrid-training approach of artificial neural network in modelling the properties of concrete containing steel fibre extracted from waste tyres

The study presents a comparative approach between Response Surface Methodology (RSM) and hybridized Genetic Algorithm of Artificial Neural Network (GA-ANN) in predicting the water absorption, compressive strength, flexural strength, split tensile strength and slump for steel fibre reinforced concret...

Full description

Bibliographic Details
Main Authors: Temitope F. Awolusi, Oluwaseyi L. Oke, Olufunke O. Akinkurolere, Olumoyewa D. Atoyebi
Format: Article
Language:English
Published: Taylor & Francis Group 2019-01-01
Series:Cogent Engineering
Subjects:
response surface methodology
hybrid
genetic algorithm artificial neural network
concrete
flexural strength
steel fibre reinforced concrete
civil engineering
Online Access:http://dx.doi.org/10.1080/23311916.2019.1649852

Similar Items

Similar Items