On Interpretation of Fuzzy Cognitive Maps Trained to Model Time Series

被引：0

作者：

Homenda, Wladyslaw ^{[1
]}

Jastrzebska, Agnieszka ^{[2
]}

Pedrycz, Witold ^{[3
,4
]}

机构：

[1] Univ Bialystok, Fac Econ & Informat Vilnius, Kalvariju G 135, LT-08221 Vilnius, Lithuania

[2] Warsaw Univ Technol, Fac Math & Informat Sci, PL-00662 Warsaw, Poland

[3] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland

[4] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6R 2G7, Canada

来源：

2014 4th World Congress on Information and Communication Technologies (WICT) | 2014年

关键词：

Fuzzy Cognitive Map; interpretation of Fuzzy Cognitive Map; time series; PREDICTION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The article analyzes consecutive phases of time series modelling with Fuzzy Cognitive Maps. The subject of interest are features determining models of good quality. First, we present the procedure: design phase, learning phase, and in the end - application. The discussion is illustrated with experiments on two synthetic time series. We have shown that the design phase determines qualitative and quantitative effectiveness of modelling. We have addressed effects of misdesigns: too large, too small or unfit at all maps on modelling quality.

引用

页码：152 / 157

页数：6

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