TY - GEN
T1 - Structural design of confined masonry buildings using artificial neural networks
AU - Sicha Pillaca, Juan Carlos
AU - Molina Ramirez, Alexander
AU - Vasquez, Victor Arana
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/30
Y1 - 2020/9/30
N2 - The aim of this article is to use artificial neural networks (ANN) to perform the structural design of confined masonry buildings. ANN is easy to operate and allows to reduce the time and cost of seismic designs. To generate the artificial neural network, training models (traditional confined masonry designs) are used to identify the input and output parameters. From this, the final architecture and activation functions are defined for each layer of the ANN. Finally, ANN training is carried out using the backpropagation algorithm to obtain the matrix of weights and thresholds that allow the network to operate and provide preliminary structural designs with a 10% margin of error, with respect to the traditional design, in the dimensions and reinforcements of the structural elements.
AB - The aim of this article is to use artificial neural networks (ANN) to perform the structural design of confined masonry buildings. ANN is easy to operate and allows to reduce the time and cost of seismic designs. To generate the artificial neural network, training models (traditional confined masonry designs) are used to identify the input and output parameters. From this, the final architecture and activation functions are defined for each layer of the ANN. Finally, ANN training is carried out using the backpropagation algorithm to obtain the matrix of weights and thresholds that allow the network to operate and provide preliminary structural designs with a 10% margin of error, with respect to the traditional design, in the dimensions and reinforcements of the structural elements.
KW - artificial intelligence
KW - artificial neural networks
KW - confined masonry
KW - structural design
UR - http://www.scopus.com/inward/record.url?scp=85096593247&partnerID=8YFLogxK
U2 - 10.1109/CONIITI51147.2020.9240404
DO - 10.1109/CONIITI51147.2020.9240404
M3 - Conference contribution
AN - SCOPUS:85096593247
T3 - 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings
BT - 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings
A2 - Martinez, Monica Andrea Rico
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - 2020 International Conference on Innovation and Trends in Engineering, CONIITI 2020
Y2 - 30 September 2020 through 2 October 2020
ER -