Forecasting GDP Growth Based on Ant Colony Clustering Algorithm and RBF Neural Network

被引：0
|
作者：
Zhao, Jianna [1 ]
Wang, Xinying [1 ]
Wu, Zhuozheng [1 ]
机构：
[1] N China Elect Power Univ, Baoding 071003, Hebei Province, Peoples R China
来源：
2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2008年
关键词：
ant colony Algorithm; RBF neural network; GDP forecast;
D O I：
暂无
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 order to forecast GDP growth much more accurate, a hybrid intelligent system is applied to improve the precision of forecasting, which combines Ant Colony Clustering Algorithm (ACCA) and RBF neural network. At first, we can make use of ACCA to cluster the data. And then, this clustered data is used to develop classification rules and train RBF neural network. The effectiveness of our methodology was verified by experiment data.
引用
收藏
页码：1839 / 1843
页数：5
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