Analysis of Time-Series Data Using the Rough Set

被引：0

作者：

Matsumoto, Yoshiyuki ^{[1
]}

Watada, Junzo ^{[2
]}

机构：

[1] Shimonoseki City Univ, 2-1-1 Daigaku Cho, Shimonoseki, Yamaguchi, Japan

[2] Waseda Univ, 2-7 Hibikino, Kitakyushu, Fukuoka, Japan

来源：

INNOVATION IN MEDICINE AND HEALTHCARE 2015 | 2016年 / 45卷

关键词：

D O I：

10.1007/978-3-319-23024-5_13

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Rough set theory was proposed by Z. Pawlak in 1982. This theory has high capability to mine knowledge based on decision rules from a database, a web base, a set and so on. The decision rule is widely used for data analysis as well. In this paper the decision rule is employed to reason for an unknown object. That is, the rough set theory is applied to analysis of economic time series data. An example shown in the paper indicates how to acquire knowledge from time series data. At the end we suggest its application to predictions.

引用

页码：139 / 148

页数：10

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