DocumentCode
2740601
Title
Dam´s Safety Monitoring Statistical Model Optimization Basing on The GA and AIC
Author
Wu, Xinmiao ; Qie, Zhihong ; Liu, Hongquan ; Furuta, Hitoshi
Author_Institution
Tianjin Univ.
Volume
2
fYear
0
fDate
0-0 0
Firstpage
7855
Lastpage
7859
Abstract
It is difficult to select influence factors when the dam´s monitoring model is built, so the Akaike information criterion (AIC) used in the field of information statistics is introduced. Both the fitting to modeling data and prediction precision to other data are considered in the AIC formula. The optimization method basing on GA and AIC is introduced. The method is applied to practical engineering, and the comparison with multiple regression, stepwise regression and neural network model shows the monitoring model optimized by the method can reach higher fitting and prediction precision by lesser factors and data
Keywords
dams; genetic algorithms; monitoring; power engineering computing; safety systems; statistical analysis; Akaike information criterion; dam safety monitoring; data fitting; data modeling; data prediction precision; genetic algorithm; information statistics; statistical model optimization; Agriculture; Electronic mail; Fitting; Informatics; Minimax techniques; Monitoring; Optimization methods; Predictive models; Safety; Statistics; AIC; Genetic Algorithm; dam; monitoring model; optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1713499
Filename
1713499
Link To Document