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Conjugate Cellular Automata and Neural Network Approach: Failure Load Prediction of Masonry Panels
Joint Authors
Glushakova, Iuliia
Liu, Qihan
Zhang, Yu
Zhou, Guangchun
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-11
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The intricate interplay between the microscopic constituents and their macroscopic properties for masonry structures complicates their failure analysis modelling.
A composite strategy incorporating neural network (NN) and cellular automata (CA) is developed to predict the failure load for masonry panels with and without openings subjected to lateral loadings.
The discretized panels are modelled by the CA methodology using nine neighbour cells, which derive their state values from geometric parameters and opening location placement for the panels.
An identification coefficient dictated by these geometric parameters and experimental data is fed together as the input training data for the NN.
The NN uses a backpropagation algorithm and two hidden layers with sigmoid activation functions to predict failure loads.
This method achieves greater accuracy in prediction when compared with the yield line and finite elemental analysis (FEA) methods.
The results attained elucidate the feasibility of the current methodology to complement conventional approaches such as FEA to provide additional insight into the failure mechanism of masonry panels under varied loading conditions.
American Psychological Association (APA)
Glushakova, Iuliia& Liu, Qihan& Zhang, Yu& Zhou, Guangchun. 2020. Conjugate Cellular Automata and Neural Network Approach: Failure Load Prediction of Masonry Panels. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1125718
Modern Language Association (MLA)
Glushakova, Iuliia…[et al.]. Conjugate Cellular Automata and Neural Network Approach: Failure Load Prediction of Masonry Panels. Advances in Civil Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1125718
American Medical Association (AMA)
Glushakova, Iuliia& Liu, Qihan& Zhang, Yu& Zhou, Guangchun. Conjugate Cellular Automata and Neural Network Approach: Failure Load Prediction of Masonry Panels. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1125718
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1125718