Optimising Neural Networks for Identification of Wood Defects Using the Bees Algorithm

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 s...

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Bibliographic Details
Published in2006 4th IEEE International Conference on Industrial Informatics pp. 1346 - 1351
Main Authors Pham, D.T., Soroka, A.J., Ghanbarzadeh, A., Koc, E., Otri, S., Packianather, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2006
Subjects
Ant colony optimization
Bonding
Genetic algorithms
Neural networks
Particle swarm optimization
Polynomials
Pulp manufacturing
Robustness
Search methods
Semiconductor optical amplifiers
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ISBN9780780397002
0780397002
ISSN1935-4576
DOI10.1109/INDIN.2006.275855

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Summary: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.
ISBN:9780780397002
0780397002
ISSN:1935-4576
DOI:10.1109/INDIN.2006.275855