Analysis using rough set of time series data including a large variation

Author

Matsumoto, Yoshiyuki ; Watada, Junzo

Author_Institution

Fac. of Econ., Shimonoseki City Univ., Shimonoseki, Japan

fYear

2014

Firstpage

1378

Lastpage

1381

Abstract

Rough set theory was proposed by Z. Pawlak in 1982. This theory can mine knowledge granules through a decision rule from a database, a web base, a set and so on. The decision rule is used for data analysis as well. And we can apply the decision rule to reason, estimate, evaluate, or forecast an unknown object. In this paper, the rough set theory is used to analysis of time series data. Knowledge granules are minded from the data set of tick-wise price fluctuations. We acquire knowledge from the time-series data including large variation. And we compare the data including large variation and normal data.

Keywords

data analysis; data mining; database management systems; decision making; rough set theory; time series; Web base; data analysis; database; decision rule; knowledge granule mining; rough set theory; tick-wise price fluctuations; time series data; Approximation methods; Companies; Knowledge acquisition; Market research; Rough sets; Time series analysis; knowledge acuisition; rough sets; time series data;

fLanguage

English

Publisher

ieee

Conference_Titel

Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on

Type

conf

DOI

10.1109/SCIS-ISIS.2014.7044842

Filename

7044842