An unsupervised neural network for stock prediction

被引：0

作者：

Chan, TKY ^{[1
]}

Tan, EC ^{[1
]}

Haralalka, N ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore

来源：

8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING | 2001年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The unsupervised Kohonen Networks equipped with Short Term Memory and Random Walk Breakout are used with straight-line equation as the curve fitting algorithm to predict the stock prices. According to the results obtained, the unsupervised networks do not have that high accuracy of prediction in general because of the constraint on the fixed number of patterns that they can recognize. However, they provide the fastest time output and thus are very useful in time critical situations.

引用

页码：768 / 771

页数：4

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