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Description and classification of granular time series

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Abstract

The study is concerned with a concept and a design of granular time series and granular classifiers. In contrast to the plethora of various models of time series, which are predominantly numeric, we propose to effectively exploit the idea of information granules in the description and classification of time series. The numeric (optimization-oriented) and interpretation abilities of granular time series and their classifiers are highlighted and quantified. A general topology of the granular classifier involving a formation of a granular feature space and the usage of the framework of relational structures (relational equations) in the realization of the classifiers is presented. A detailed design process is elaborated on along with a discussion of the pertinent optimization mechanisms. A series of experiments is covered leading to a quantitative assessment of the granular classifiers and their parametric analysis.

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Acknowledgments

This paper was funded by King Abdulaziz University, under Grant No. (6-4-1432/HiCi). The authors, therefore, acknowledge technical and financial support of KAU.

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Authors and Affiliations

  1. Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia

    Rami Al-Hmouz, Witold Pedrycz, Abdullah Balamash & Ali Morfeq

  2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta , T6R 2V4, Canada

    Witold Pedrycz

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Witold Pedrycz

Authors
  1. Rami Al-Hmouz
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  2. Witold Pedrycz
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  3. Abdullah Balamash
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  4. Ali Morfeq
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Corresponding author

Correspondence to Rami Al-Hmouz.

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Communicated by V. Loia.

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Al-Hmouz, R., Pedrycz, W., Balamash, A. et al. Description and classification of granular time series. Soft Comput 19, 1003–1017 (2015). https://doi.org/10.1007/s00500-014-1311-z

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  • DOI: https://doi.org/10.1007/s00500-014-1311-z

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