SAPSO neural network for inspection of non-development hatching eggs

Authors:
Yu Zhi-hong;Wang Chun-guang;Feng Jun-qing
Affiliations:
College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Huhhot, China;College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Huhhot, China;College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Huhhot, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

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Abstract

Detection fertility and development in hatchery eggs could increase efficiency in commercial hatcheries. A new algorithm named simulated annealing particle swarm optimization algorithm (SAPSO) is proposed, and it is used to optimize topology structure of multi-layer feedback forward neural network for classification of hatching eggs. Trained and tested by a great deal of samples, a reasonable neural network model is obtained. Its performance is measured in terms of two parameters: short computing time and accuracy in the classification process.