The Study of PNN Quality Control Method Based on Genetic Algorithm

Abstract:

For the probability neural network (PNN) algorithm is the non-surveillance's pattern taxonomic approach, the work load major problem, moreover the category number's selection will affect the cluster performance. How to optimize PNN enabled it to play a more effective role in the classified question, this paper proposed one use genetic algorithm optimization probability neural network method: introduction the auto-adapted mechanism genetic algorithm, to the probability neural network's parameter carries on the training, formed the supervised learning probability neural network based on the genetic algorithm, overcome the probability neural network existing algorithm flaw. Then introduces this model in the quality control, guaranteed that the production process is at the control state, achieves the quality control goal. Carries on the test through the simulation experiment to this algorithm, and with the probability neural network, the BP neural network carries on the comparative analysis, proved this method accuracy is high.

• Periodical: Key Engineering Materials (Volumes 467-469)
• Pages: 2103-2108
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.467-469.2103
• Online since: February 2011
• Authors: Jun Li, Shu Lin Kan, Peng Yu Liu
• Keywords: BP Network, Genetic Algorithm (GA), Non-Supervised, PNN, Quality Control, Simulation Training

References

[1] Fu Jun, HeWei Zhang, Hongcai: a Study of Fault Diagnosis Based on Bayesian. Journal of Shanghai Maritime University, Vol. 22 (3), (2001), pp.68-77.

[2] Cai Qulin: Pattern recognition based on probability neural network: [master's degree paper]. Changsha, National University of Defense Technology, (2006).

[3] Rao Wenbi, Cheng Hongbin: Realization of Structure damage neural network identification system. Wuhan University of Science and Technology journal, Vol. 24(1) (2002), pp.28-30.

[4] Zhou Ming, Sun Shudong: Principle and Application of Genetic Algorithm, Beijing: The Defense industry Publishing house, (1999).

[5] Cai Qulin, Liu Puyin: a Kind of New Probability Neural Network the Supervised Learning Algorithm. Fuzzy system and mathematics, Vol. 20(6) (2006), pp.83-87.