A rough set approach to events prediction in multiple time series

Fatma-Ezzahra Gmati, Salem Chakhar, Wided Lejouad Chaari , Huijing Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

This paper introduces and illustrates a rough-set based approach to event prediction in multiple time series. The proposed approach uses two different versions of rough set theory to predict events occurrences and intensities. First, classical Indiscernibility relation-based Rough Set Approach (IRSA) is used to predict event classes and occurrences. Then, the Dominance-based Rough Set Approach (DRSA) is employed to predict the intensity of events. This paper presents the fundamental of the proposed approach and the conceptual architecture of a framework implementing this approach.
Original languageEnglish
Title of host publicationRecent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Proceedings
Subtitle of host publication31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Montreal, QC, Canada, June 25-28, 2018, Proceedings
EditorsMalek Mouhoub, Samira Sadaoui, Otmane Ait Mohamed, Moonis Ali
PublisherSpringer International Publishing
Pages796-807
Number of pages12
ISBN (Electronic)978-3-319-92058-0
ISBN (Print)978-3-319-92057-3
DOIs
Publication statusPublished - Jun 2018
Event31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: IEA/AIE 2018 - Montreal, Canada
Duration: 25 Jun 201828 Jun 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10868
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems
Country/TerritoryCanada
CityMontreal
Period25/06/1828/06/18

Keywords

  • Event Prediction
  • Multiple Time Series
  • Rough Sets
  • Dominance-based Rough Set Approach

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