Open AccessPrediction of a singly reinforced concrete beam steel using artificial neural network
Author(s) -
S O A Olawale,
Olutosin Peter Akintunde,
M O Afolabi,
Oluwole A. Agbede
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1036/1/012057
Subject(s) - artificial neural network , beam (structure) , structural engineering , computer science , matlab , reinforcement , code (set theory) , backpropagation , artificial intelligence , engineering , set (abstract data type) , programming language , operating system
This paper presents the prediction of a singly reinforced concrete beam using Artificial Neural Networks (ANN). The method was adopted for cost optimization of the structural element and compared with the requirements of Eurocode 2 design. The code provisions for the design of a singly reinforced beam can vary from place to place. The use of a system immune from the code variation is an excellent means of predicting the reinforcement’s need of a rectangular concrete beam. In this work, an artificial neural network (ANN) is employed to forecast the reinforcement of such a beam. Artificial neural network has the potential to simulate the data that are hard to produce in arithmetical analysis. The scheme was established using the MATLAB tool kit. The design variables were the depth of the beam, the width of the beam, and the moments. A forward pass supervised backward propagation training. The regression analysis of the results is one to one match. The predicted and target values are completely in accord.