Title :
Determination of Safety Assessment Factors Weight Based on Genetic Neural Networks
Author :
Zhijun, Wang ; Zhongliang, Lu
Author_Institution :
Sch. of Safety Sci. & Eng., Henan Polytech. Univ., Jiaozuo, China
Abstract :
A new method of neural networks based on genetic algorithm is put forward for factors weight determination of safety assessment in the paper. The procedure on optimizing neural networks by genetic algorithm is expatiated. How to pick up the information of factors weight from the network link weight after training is analyzed in detail. The influence of primary network weight on final determination result could be eliminated by symbolic statistics. Experiment shows that the method is highly operational with high accuracy. This method can determine the influence of factors on effect-variable effectively and evaluate the behavior of system safety.
Keywords :
genetic algorithms; neural nets; production engineering computing; safety systems; statistics; factors weight determination; genetic algorithm; genetic neural networks; safety assessment; symbolic statistics; Artificial intelligence; Artificial neural networks; Biological neural networks; Computer networks; Genetic algorithms; Genetic engineering; Information analysis; Neural networks; Safety; Statistics; determination; factors weight; genetic algorithm; neural networks; safety assessment;
Conference_Titel :
Information and Computing (ICIC), 2010 Third International Conference on
Conference_Location :
Wuxi, Jiang Su
Print_ISBN :
978-1-4244-7081-5
Electronic_ISBN :
978-1-4244-7082-2
DOI :
10.1109/ICIC.2010.20
