Optimisation of convolutional neural network architecture using genetic algorithm for the prediction of adhesively bonded joint strength

dc.contributor.authorArhore, Edore G.
dc.contributor.authorYasaee, Mehdi
dc.contributor.authorDayyani, Iman
dc.date.accessioned2022-09-20T09:54:36Z
dc.date.available2022-09-20T09:54:36Z
dc.date.issued2022-09-02
dc.description.abstractThe classical method of optimising structures for strength is computationally expensive due to the requirement of performing complex non-linear finite element analysis (FEA). This study aims to optimise an artificial neural network (ANN) architecture to perform the task of predicting the strength of adhesively bonded joints in place of non-linear FEA. A manual multi-objective optimisation was performed to find a suitable ANN architecture design space. Then a genetic algorithm optimisation of the reduced design space was conducted to find an optimum ANN architecture. The generated optimum ANN architecture predicts efficiently the strength of adhesively bonded joints to a high degree of accuracy in comparison with the legacy method using FEA with a 93% savings in computational cost.en_UK
dc.identifier.citationArhore EG, Yasaee M, Dayyani I. (2022) Optimisation of convolutional neural network architecture using genetic algorithm for the prediction of adhesively bonded joint strength. Structural and Multidisciplinary Optimization, Issue 65, September 2022, Article number 256en_UK
dc.identifier.issn1615-147X
dc.identifier.urihttps://doi.org/10.1007/s00158-022-03359-x
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18457
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectadhesive jointsen_UK
dc.subjectconvolutional neural networken_UK
dc.subjectgenetic algorithmen_UK
dc.subjectcomposite adherenden_UK
dc.subjectlightweight designen_UK
dc.titleOptimisation of convolutional neural network architecture using genetic algorithm for the prediction of adhesively bonded joint strengthen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
adhesively_bonded_joint_strength-2022.pdf
Size:
3.96 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description: