Analysis of time-series data using the rough set

Yoshiyuki Matsumoto; Junzo Watada

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

Analysis of time-series data using the rough set

Yoshiyuki Matsumoto^*, Junzo Watada

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	Smart Innovation, Systems and Technologies
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	139-148
Number of pages	10
Volume	45
ISBN (Print)	9783319230238
DOIs	https://doi.org/10.1007/978-3-319-23024-5_13
Publication status	Published - 2016
Event	3rd KES International Conference on Innovation in Medicine and Healthcare, InMed 2015 - Kyoto, Japan Duration: 2015 Sept 11 → 2015 Sept 12

Publication series

Name	Smart Innovation, Systems and Technologies
Volume	45
ISSN (Print)	21903018
ISSN (Electronic)	21903026

Other

Other	3rd KES International Conference on Innovation in Medicine and Healthcare, InMed 2015
Country/Territory	Japan
City	Kyoto
Period	15/9/11 → 15/9/12

ASJC Scopus subject areas

Computer Science(all)
Decision Sciences(all)

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

Cite this

Matsumoto, Y & Watada, J 2016, Analysis of time-series data using the rough set. in Smart Innovation, Systems and Technologies. vol. 45, Smart Innovation, Systems and Technologies, vol. 45, Springer Science and Business Media Deutschland GmbH, pp. 139-148, 3rd KES International Conference on Innovation in Medicine and Healthcare, InMed 2015, Kyoto, Japan, 15/9/11. https://doi.org/10.1007/978-3-319-23024-5_13

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AB - 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.

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Analysis of time-series data using the rough set

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