Experimental Evaluation of Straight Line Programs for Hydrological Modelling with Exogenous Variables

被引：2

作者：

Rueda Delgado, Ramon ^{[1
]}

Baca Ruiz, Luis G. ^{[1
]}

Jimeno-Saez, Patricia ^{[2
]}

Pegalajar Cuellar, Manuel ^{[1
]}

Pulido-Velazquez, David ^{[3
]}

Del Carmen Pegalajar, Mara ^{[1
]}

机构：

[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, C Pdta Daniel Saucedo Aranda Sn, Granada, Spain

[2] Catholic Univ San Antonio, Dept Civil Engn, Campus Jeronimos S-N, Murcia 30107, Spain

[3] Inst Geol & Minero Espana, 4 Edificio Zulema Bajo, Granada 18006, Spain

来源：

HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2017 | 2017年 / 10334卷

关键词：

Genetic programming; Straight line programs; Symbolic regression; Modeling hydrological balance;

D O I：

10.1007/978-3-319-59650-1_38

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The estimation of the future streamflows is one of the main research topics in hydrology and a very important task for water resources management. The aim of this work is to use symbolic regression in order to model the hydrological balance. Specifically, we use genetic programming to solve the symbolic regression problem. Nevertheless, in this work we use Straight Line Programs instead of trees to encode algebraic expression. Results shows that this representation for algebraic expressions could improve the results in both accuracy and computational time.

引用

页码：447 / 458

页数：12

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