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

Volume

1

fYear

2010

fDate

4-6 June 2010

Firstpage

54

Lastpage

57

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICIC.2010.20

Filename

5514238