Optimizing truss members using Machine Learning

\nThis paper aims to produce an optimization methodology for a truss for minimal stress on critical sections using Machine learning models. This is done by varying the height and length of the truss span and applying live loads on different joints. The optimization of the truss is done through feed forward with back propagation artificial neural network model, The optimized truss is modelled and analysed using finite element and stiffness software. The paper presents the results and identifies the best dimensions for the truss design with a safety factor.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-08-08
DOI
https://doi.org/10.1051/e3sconf/202455904010/pdf
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimizing truss members using Machine Learning

Springer Link (Chiba Institute of Technology)
Mycorrhizal Fungi and Plant Interactions
article

Optimizing truss members using Machine Learning

article en

Abstract

\nThis paper aims to produce an optimization methodology for a truss for minimal stress on critical sections using Machine learning models. This is done by varying the height and length of the truss span and applying live loads on different joints. The optimization of the truss is done through feed forward with back propagation artificial neural network model, The optimized truss is modelled and analysed using finite element and stiffness software. The paper presents the results and identifies the best dimensions for the truss design with a safety factor.\n

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 59%
Mycorrhizal Fungi and Plant Interactions
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Optimizing truss members using Machine Learning · Springer Link (Chiba Institute of Technology) (2024) | TGRS Research Map | TGRS