Classifying weather time series using featurebased approach

Shakirah Mohd Taib, Azuraliza Abu Bakar, Abdul Razak Hamdan, Sharifah Mastura Syed Abdullah

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Classification of weather time series is beneficial for weather forecasting problem. The classification can assist in identifying weather patterns for certain periods. In addition, extracting patterns from weather time series provides useful insights about the weather conditions to the domain experts. In this paper, we present the classification of weather time series using feature based approach that extracts feature vectors from the time series and performs the classification based on local and global features. The experimental results show that feature-based method with random forest performs well with more number of subsequences and may achieve comparable results with other methods.

Original languageEnglish
Pages (from-to)56-71
Number of pages16
JournalInternational Journal of Advances in Soft Computing and its Applications
Volume7
Issue numberSpecialissue3
Publication statusPublished - 2015

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Time series
Weather forecasting

Keywords

  • Feature-based method
  • Random forest
  • Time series classifcation
  • Weather time series

ASJC Scopus subject areas

  • Computer Science Applications

Cite this

Classifying weather time series using featurebased approach. / Taib, Shakirah Mohd; Abu Bakar, Azuraliza; Hamdan, Abdul Razak; Syed Abdullah, Sharifah Mastura.

In: International Journal of Advances in Soft Computing and its Applications, Vol. 7, No. Specialissue3, 2015, p. 56-71.

Research output: Contribution to journalArticle

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