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) |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Engineering Research Institutes & Centres > 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: | 05 Feb 2025 22:45 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/37633 |
Citation Data
Cited 93 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
 |
Edit Item |
Dimensions
Dimensions