Foreign exchange market forecasting using evolutionary fuzzy networks

被引：8
|
作者：
Muhammad, A
King, GA
机构：
来源：
PROCEEDINGS OF THE IEEE/IAFE 1997 COMPUTATIONAL INTELLIGENCE FOR FINANCIAL ENGINEERING (CIFER) | 1997年
关键词：
D O I：
10.1109/CIFER.1997.618939
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents an evolutionary fuzzy network method for prediction in foreign exchange markets. This research chooses the financial data used in Santa Fe time series forecasting competition, 1990-91 [Weigend' 94]. Choice of this data provides a comparative study of the previous attempts to forecast. Fuzzy systems not only provide the mechanism to integrate human linguistic knowledge into logical frame work but also provides the means to extract fuzzy rules from an observed data set. For global optimisation, Genetic Algorithms are used to adapt the parameters of the fuzzy network in order to obtain the best performance.
引用
收藏
页码：213 / 219
页数：7
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