Intelligent Adaptive Genetic Algorithm and its Application

Author

Chen, Guochu

Author_Institution

Electr. Eng. Sch., Shanghai DianJi Univ., Shanghai, China

Volume

1

fYear

2011

fDate

28-29 March 2011

Firstpage

163

Lastpage

166

Abstract

Through analyzing the operating mechanism of the genetic algorithm, intelligent adaptive genetic algorithm (IAGA) is proposed whose crossover probability and mutation probability can be adjusted adaptively. Then IAGA is applied to optimize the weights and thresholds of the forward neural network, and establish soft-sensor model of gasoline endpoint of the main fractionator of fluid catalytic cracking unit. Results show that the method proposed by this paper is feasible and effective in soft-sensing modeling of gasoline endpoint.

Keywords

genetic algorithms; neural nets; petrochemicals; petroleum industry; probability; production engineering computing; sensors; crossover probability; forward neural network; gasoline endpoint; intelligent adaptive genetic algorithm; mutation probability; soft sensor model; Adaptation model; Analytical models; Genetic algorithms; Optimization; Petroleum; Temperature distribution; Temperature measurement; adaptive; gasoline endpoint; genetic algorithms; neural network; soft sensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on

Conference_Location

Shenzhen, Guangdong

Print_ISBN

978-1-61284-289-9

Type

conf

DOI

10.1109/ICICTA.2011.49

Filename

5750581