Two-phase imputation with regional-gradient-guided bootstrapping algorithm and dynamics time warping for incomplete time series data

  • Authors:
  • Sathit Prasomphan;Chidchanok Lursinsap;Sirapat Chiewchanwattana

  • Affiliations:
  • Advance Virtual and Intelligent Computing Center, Faculty of Science, Chulalongkorn University, Thailand;Advance Virtual and Intelligent Computing Center, Faculty of Science, Chulalongkorn University, Thailand;Department of Computer Science, Khon Kaen University, Thailand

  • Venue:
  • ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
  • Year:
  • 2010

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Abstract

In this paper new algorithms with the combination between the Regional-Gradient-Guided Bootstrapping Algorithm and Dynamics Time Warping Technique for imputing incomplete time series data are proposed. The new measurement for curve similarity comparison by using the changing of slope of time series data are used. The main contribution of this paper is to propose new technique for imputing the fluctuate time series data. We compare our new method with Cubic interpolation, Multiple imputation, Windows Varies Similarity Measurement algorithms and Regional-Gradient-Guided Bootstrapping Algorithm. The experimental results showed that our new algorithms are outperform than these method.