Analysis of time-series data using the rough set

Yoshiyuki Matsumoto, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
    Title of host publicationSmart Innovation, Systems and Technologies
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages139-148
    Number of pages10
    Volume45
    ISBN (Print)9783319230238
    DOIs
    Publication statusPublished - 2016
    Event3rd KES International Conference on Innovation in Medicine and Healthcare, InMed 2015 - Kyoto, Japan
    Duration: 2015 Sep 112015 Sep 12

    Publication series

    NameSmart Innovation, Systems and Technologies
    Volume45
    ISSN (Print)21903018
    ISSN (Electronic)21903026

    Other

    Other3rd KES International Conference on Innovation in Medicine and Healthcare, InMed 2015
    CountryJapan
    CityKyoto
    Period15/9/1115/9/12

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    ASJC Scopus subject areas

    • Computer Science(all)
    • Decision Sciences(all)

    Cite this

    Matsumoto, Y., & Watada, J. (2016). Analysis of time-series data using the rough set. In Smart Innovation, Systems and Technologies (Vol. 45, pp. 139-148). (Smart Innovation, Systems and Technologies; Vol. 45). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-23024-5_13