Forecast of industrial index based on genetic neural network

被引：0
|
作者：
Yang Zhaowen [1 ]
Xie Bing [1 ]
Dai Sheng [1 ]
机构：
[1] Wuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China
来源：
Proceedings of 2005 International Conference on Innovation & Management | 2005年
关键词：
NN(Neural network); genetic algorithm; industrial index forecast;
D O I：
暂无
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
In order to make more accurate forecast results, we combine methods of genetic algorithm with BNPP in the forecast of industrial index, otherwise in the process of the forecast we use five input-variables namely weekly turnover increase and decrease piece, weekly oscillation amplitude, weekly UP/DOWN, five bargain days' EMA fluctuation, DIF fluctuation and one output-variable The Next week UP/DOWN. As to the problem of low efficiency in choosing appropriate topological structure of neural network, the introduction of genetic algorithm has improved the speed of searching for the optimum topological structure greatly in this paper.
引用
收藏
页码：101 / 107
页数：7
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