Runoff Simulation Using Artificial Intelligent Techniques

Author

Yang, Xiaohua ; Li, Yuqi

Author_Institution

State Key Lab. of Water Environ. Simulation, Beijing Normal Univ., Beijing, China

fYear

2012

fDate

1-3 June 2012

Firstpage

1

Lastpage

3

Abstract

In order to improve the computational accuracy for runoff simulation, an artificial intelligent technique, improved chaos genetic algorithm (ICGA) is proposed, in which initial population are generated by chaos mapping and searching range is automatically renewed with the excellent individuals obtained by ICGA. Its global convergence is analyzed. Its efficiency is verified by application of runoff simulation for three rainfall events. Compared with standard binary-encoded genetic algorithm (SGA), chaos genetic algorithm (CGA), ICGA has higher precision and rapider convergent speed. It is good for the global optimization in the practical runoff simulation.

Keywords

rain; artificial intelligent techniques; chaos mapping; improved chaos genetic algorithm; practical runoff simulation; rainfall events; standard binary-encoded genetic algorithm; Biological cells; Chaos; Computational modeling; Educational institutions; Genetic algorithms; Mathematical model; Optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4673-0872-4

Type

conf

DOI

10.1109/RSETE.2012.6260721

Filename

6260721