Pham, Duc Truong, Soroka, Anthony John ORCID: https://orcid.org/0000-0002-9738-9352, Ghanbarzadeh, Afshin ORCID: https://orcid.org/0000-0002-5197-9752, Koc, Ebubekir, Otri, Sameh and Packianather, Michael Sylvester ORCID: https://orcid.org/0000-0002-9436-8206 2006. Optimising neural networks for identification of wood defects using the bees algorithm. Presented at: 2006 IEEE International Conference on Industrial Informatics, Singapore, 16-18 August 2006. Proceedings of the 2006 IEEE International Conference on Industrial Informatics, Singapore, 16-18 August 2006. IEEE, pp. 1346-1351. 10.1109/INDIN.2006.275855 |
Abstract
This paper presents an application of the bees algorithm (BA) to the optimisation of neural networks for wood defect detection. This novel population-based search algorithm mimics the natural foraging behaviour of swarms of bees. In its basic version, the algorithm performs a kind of neighbourhood search combined with random search. Following a brief description of the algorithm, the paper gives the results obtained for the wood defect identification problem demonstrating the efficiency and robustness of the new algorithm.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC) |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Uncontrolled Keywords: | Ant colony optimization; Bonding; Genetic algorithms; neural networks; Particle swarm optimization; Polynomials; Pulp manufacturing; Robustness; Search methods; Semiconductor optical amplifiers |
Publisher: | IEEE |
ISBN: | 0780397002 |
Related URLs: | |
Last Modified: | 21 Oct 2022 09:46 |
URI: | https://orca.cardiff.ac.uk/id/eprint/37633 |
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