Rainfall-runoff simulation using improved evolution algorithm based on pattern search

Author

Yang, Xiaohua ; Li, Yuqi

Author_Institution

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

fYear

2012

fDate

29-31 May 2012

Firstpage

1212

Lastpage

1215

Abstract

Rainfall-runoff simulation is very important in practical environmental planning. To improve the computational accuracy for rainfall-runoff simulation, an improved evolution algorithm based on pattern search (IEAPS) is proposed, in which initial population are generated by chaos mapping and searching range is automatically renewed with the excellent individuals by pattern search. Its efficiency is verified by application of rainfall-runoff simulation for five rainfall events. Compared with standard binary-encoded genetic algorithm (SGA), pattern search algorithm (PSA), IEAPS has higher precision and rapider convergent speed. It is good for the global optimization in the practical rainfall-runoff simulation.

Keywords

genetic algorithms; geophysics computing; hydrological techniques; hydrology; rain; IEAPS; chaos mapping; computational accuracy; convergent speed; evolution algorithm; pattern search algorithm; practical environmental planning; rainfall events; rainfall-runoff simulation; standard binary-encoded genetic algorithm; Algorithm design and analysis; Biological cells; Chaos; Computational modeling; Genetic algorithms; Mathematical model; Optimization; chaos; evolution algorithm; optimization; rainfall-runoff; simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2012 Eighth International Conference on

Conference_Location

Chongqing

ISSN

2157-9555

Print_ISBN

978-1-4577-2130-4

Type

conf

DOI

10.1109/ICNC.2012.6234571

Filename

6234571