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IJMLC 2020 Vol.10(4): 507-512 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.4.965

Space Frame Optimisation with Spectral Clustering

Xinwei Zhuang and Sean Hanna

Abstract—This paper borrows the concept of spectral clustering in the computer vision field, proposes an alternative approach to optimise space frame structure. Spectral clustering was implemented to segment the whole structure into two subclusters. Then genetic algorithm was used to optimise member sizes of each subcluster separately. It is hypothesized that optimizing the structural stability for subassemblies will largely reduce the search space, which allows greater computational efficiency. The program has been developed in MATLAB and tested on differently shaped space frame structure under varied loading conditions. Results show that for a heterogeneous structure with high a level of complexity, the implementation of spectral clustering can separate the enormous search space of GA down to smaller search space, leading to faster convergence with increased the computational efficiency, while providing an equivalent or better optimisation solution.

Index Terms—Computational efficiency, genetic algorithm, space frame structure, spectral clustering, structural optimization.

Xinwei Zhuang was with University College London, London, WC1E 6BT UK (e-mail: ucqbxz9@ucl.ac.uk).
Sean Hanna is with University College London, London, WC1E 6BT UK (e-mail: s.hanna@ucl.ac.uk).

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Cite: Xinwei Zhuang and Sean Hanna, "Space Frame Optimisation with Spectral Clustering," International Journal of Machine Learning and Computing vol. 10, no. 4, pp. 507-512, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net


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