USING FUZZY AND FRACTAL METHODS FOR ANALYZING MARKET TIME SERIES

被引：0

作者：

Kroha, P. ^{[1
]}

Lauschke, M. ^{[1
]}

机构：

[1] Univ Technol, Dept Comp Sci, Str Nationen 62, D-09111 Chemnitz, Germany

来源：

ICFC 2010/ ICNC 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON FUZZY COMPUTATION AND INTERNATIONAL CONFERENCE ON NEURAL COMPUTATION | 2010年

关键词：

Time series; Fuzzy-controller; Fractal analysis; Market data;

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：

In this contribution, we investigate the possibilities of using fuzzy and fractal methods for analyzing time series of market data. First, we implemented and tested a fuzzy component that provides fuzzyfication by the Mamdani Larsen inference method with static rules using not only Gauss but also Cauchy and Mandelbrot distribution. Second, we implemented and tested a fractal component that provides fuzzy clustering by the Takagi Sugeno method with dynamic fuzzy rules. Looking for an optimum, we simulated many parameter combinations and compared the results. We present some interesting results of our experiments.

引用

页码：85 / 92

页数：8

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