Paper Info
Title
Shear strength of SFRCB without stirrups simulation: implementation of hybrid artificial intelligence model
Abstract
Recent developments on shear strength (Vf) of steel fiber-reinforced concrete beam (SFRCB) simulation have been shifted to the implementation of the computer aid advancements. The current study is attempted to explore new hybrid artificial intelligence (AI) model called integrative support vector regression with firefly optimization algorithm (SVR-FFA) for shear strength prediction of SFRCB. The developed hybrid predictive model is constructed using laboratory experimental data set gathered from the literature and belongs to the shear failure capacity. The related beam dimensional and concrete properties are utilized as input attributes to predict Vf. The proposed SVR-FFA model is validated against classical SVR model and eight empirical formulations obtained from published researches. The attained results of the proposed hybrid AI model exhibited a reliable resultant performance in terms of prediction accuracy. Based on the examined root-mean-square error (RMSE) and the correlation coefficient (R2) over the testing phase, SVR-FFA achieved (RMSE ≈ 0.25 MPa) and (R2 ≈ 0.96).
Year
DOI
Venue
2020
10.1007/s00366-018-0681-8
Engineering with Computers
Keywords
Field
DocType
Hybrid intelligence model, Shear strength, Steel fiber-reinforced concrete beam, Empirical formulations
Correlation coefficient,Shear strength,Experimental data,Support vector machine,Mean squared error,Beam (structure),Optimization algorithm,Artificial intelligence,Firefly protocol,Mathematics
Journal
Volume
Issue
ISSN
36
1
1435-5663
Citations 
PageRank 
References 
4
0.55
12
Authors
6
Name
Order
Citations
PageRank
Abeer A. Al-Musawi140.55
Afrah A. H. Alwanas240.55
Sinan Q. Salih340.55
Zainab Hasan Ali440.55
Minh Tung Tran540.55
zaher mundher yaseen6359.67