Forecasting using genetic programming

被引：8
|
作者：
Sheta, AF [1 ]
Mahmoud, A [1 ]
机构：
[1] King Fahd Univ Petr & Minerals, Dept Syst Engn, Dhahran 31261, Saudi Arabia
来源：
PROCEEDINGS OF THE 33RD SOUTHEASTERN SYMPOSIUM ON SYSTEM THEORY | 2001年
关键词：
D O I：
10.1109/SSST.2001.918543
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, two models for forecasting the Nile River flow have been developed. A traditional linear Auto-Regressive (AR) model and a Genetic Programming (GP) based model are presented. The performance of both the AR and the GP models were tested using a set of measurements recorded at the Dongola station located in the Northern Sudan. A significant improvements of the error when using GP model for forecasting was achieved.
引用
收藏
页码：343 / 347
页数：5
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