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 :
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