Stock Market Forecast Based on Wavelet Neural Network Optimized by Cuckoo Search

被引：0
|
作者：
Zhi, Hua [1 ]
Zhang, Jinghuan [2 ]
Xue, Zheng [2 ]
Zhang, Yan [2 ]
机构：
[1] Univ Lanzhou, Sch Informat Sci & Engn, Lanzhou, Gansu, Peoples R China
[2] Jiuquan Satellite Launch Ctr, Jiuquan, Gansu, Peoples R China
来源：
PROCEEDINGS OF 2017 8TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2017) | 2017年
关键词：
Cuckoo Search; Wavelet Neural Network; Stock Market Forecast; LEVY FLIGHTS;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
As a typical nonlinear deterministic dynamical system, stock market can be predicted by Wavelet Neural Network. Since Cuckoo Search is a new heuristic bionic group intelligent optimization algorithm, it can be widely used in various optimization problems. In this paper, we use Cuckoo Search (CS) to optimize the initial parameters of wavelet neural network. Results of the experiment show that the optimized CS-WNN has higher prediction accuracy than the traditional WNN in stock market forecast.
引用
收藏
页码：560 / 562
页数：3
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