Volume 8, Issue 3 (10-2018)
IJOCE 2018, 8(3): 453-467 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Suguna K, Raghunath P N, Karthick J, Uma Maheswari R. ANN BASED MODELING FOR HIGH STRENGTH CONCRETE BEAMS WITH SURFACE MOUNTED FRP LAMINATES. IJOCE 2018; 8 (3) :453-467
URL: http://ijoce.iust.ac.ir/article-1-355-en.html
URL: http://ijoce.iust.ac.ir/article-1-355-en.html
Abstract: (17367 Views)
This study focuses on using an artificial neural network (ANN) based model for predicting the performance of high strength concrete (HSC) beams strengthened with surface mounted FRP laminates. Eight input parameters such as geometrical properties of the beam and mechanical properties of FRP laminates were considered for this study. Back propagation network with Lavenberg-Marquardt algorithm has been chosen for the proposed network, which has been implemented using the programming package MATLAB. In the present study, comparison has been made between the experimental results and those predicted through neural network modeling. The amount of MAPE and RMSE were predicted and were found to be acceptable range. The statistical indicators such as correlation co-efficient (r) and co-efficient of determination (R2) were also predicted to estimate the accuracy of results obtained through ANN modeling. The results predicted through ANN modeling exhibit good correlation with the experimental results.
Type of Study: Research |
Subject:
Optimal design
Received: 2017/12/2 | Accepted: 2017/12/2 | Published: 2017/12/2
Received: 2017/12/2 | Accepted: 2017/12/2 | Published: 2017/12/2
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
