Research on the genetic regression model of Earth-rock dam safety monitoring and its application

Author

Chun-Di Si ; Ji-Jian Lian ; Zhi-Hong Qie ; Shu-Quan Li ; Xin-Miao Wu

Author_Institution

Tianjin Univ., China

Volume

5

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

2874

Abstract

In this paper, the factors which influence the piezometric level of Earth-rock dams are combined randomly by using a genetic algorithm to do selective preference. A new genetic regression model is established based on considering the comprehensive influence of fitting and prediction accuracy in fitness function. Through analyzing the seepage monitoring data of Dong Wu Shi Reservoir, it is shown that the prediction accuracy of this method is better than that of the general statistical regression.

Keywords

dams; data analysis; environmental science computing; genetic algorithms; regression analysis; reservoirs; Dong Wu Shi Reservoir; Earth-rock dam safety monitoring; fitness function; genetic algorithm; genetic regression model; piezometric level; seepage monitoring data analysis; statistical regression; Accuracy; Atmospheric modeling; Equations; Genetic algorithms; Linear regression; Monitoring; Predictive models; Safety; Semiconductor process modeling; Stability; Earth-rock dam; fitting accuracy; genetic regression model; prediction accuracy; safety monitoring;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527433

Filename

1527433