Title :
Application of genetic algorithm combining operation tree (GAOT) to stream-way transition
Author :
Chen, Kuan-ting ; Kou, Chang-huan ; Chen, Li ; Ma, Shih-wei
Author_Institution :
Dept. of Civil Eng., Chung Hua Univ., Hsinchu, Taiwan
Abstract :
The main purpose of this paper is to predict stream-way transition with genetic algorithm (GA) combined with the Operation Tree (OT), called GAOT. Therefore, the downstream stream-way transition according to the upstream conditions is forecasted by GAOT. Five main factors affect the stream-way transition including inflow position, inflow angle, slope, flow discharge, and sand content of suspended sediment were chosen as input variables. We selected two important cross sections nearby a damaged bridge of Ta-Chia River in Taiwan as a case study. The results show that GAOT has better performance than the traditional linear regression (LR) method.
Keywords :
genetic algorithms; regression analysis; rivers; trees (mathematics); GAOT; Ta-Chia River; Taiwan; damaged bridge; downstream stream-way transition; flow discharge; genetic algorithm combining operation tree; inflow angle; inflow position; linear regression method; sand content; slope; suspended sediment; Abstracts; Biological information theory; Biological system modeling; Geology; Testing; Training; Genetic algorithm; Linear regression; Operation tree; Stream-way transition; Ta-Chia River;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1484-8
DOI :
10.1109/ICMLC.2012.6359644