Fuzzy-based shapelets for mining climate change time series patterns

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

3 Citations (Scopus)

Abstract

It is difficult to identify visualized multi-climate change patterns from time series data due to the fact that the data begin to look similar over time. Traditionally, time series weather patterns are presented in the form of a linear graph, which is limited to discovering understandable climate change patterns. On the other hand, the Symbolic Aggregate Approximation (SAX) algorithm based on the Piecewise Aggregate Approximation (PAA), which is known as a popular method to solve this problem, has its limitations. Therefore, the aim of this research was to propose a fuzzy-based symbolic data representation, known as a Shapelet Patterns Algorithm (SPA), in order to come up with a Shapelet Pattern (SP) for climate change. The shapelet pattern was able to visualize climate change patterns in the form of coloured shapes to indicate annual changes in temperature patterns, such as cool, warm, hot and very hot. The experiment used the climate change data for 1985-2008 gathered from the Petaling Jaya station in the state of Selangor, Malaysia. The shapelet patterns revealed seven types of climate change patterns and presented detailed information on climate changes that can aid climate change experts in better decision making.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages38-50
Number of pages13
Volume9429
ISBN (Print)9783319259383, 9783319259383
DOIs
Publication statusPublished - 2015
Event4th International Visual Informatics Conference, IVIC 2015 - Bangi, Malaysia
Duration: 17 Nov 201519 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9429
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Visual Informatics Conference, IVIC 2015
CountryMalaysia
CityBangi
Period17/11/1519/11/15

Fingerprint

Climate Change
Climate change
Time series
Mining
Approximation algorithms
Malaysia
Time Series Data
Weather
Decision making
Annual
Approximation Algorithms
Decision Making

Keywords

  • Climate change
  • Climate shapelet patterns
  • Fuzzy logic
  • Symbolic data representation
  • Time series

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Al-Dharhani, G. S., Ali Othman, Z., Abu Bakar, A., & Syed Abdullah, S. M. (2015). Fuzzy-based shapelets for mining climate change time series patterns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9429, pp. 38-50). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9429). Springer Verlag. https://doi.org/10.1007/978-3-319-25939-0_4

Fuzzy-based shapelets for mining climate change time series patterns. / Al-Dharhani, Ghassan Saleh; Ali Othman, Zulaiha; Abu Bakar, Azuraliza; Syed Abdullah, Sharifah Mastura.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9429 Springer Verlag, 2015. p. 38-50 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9429).

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

Al-Dharhani, GS, Ali Othman, Z, Abu Bakar, A & Syed Abdullah, SM 2015, Fuzzy-based shapelets for mining climate change time series patterns. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9429, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9429, Springer Verlag, pp. 38-50, 4th International Visual Informatics Conference, IVIC 2015, Bangi, Malaysia, 17/11/15. https://doi.org/10.1007/978-3-319-25939-0_4
Al-Dharhani GS, Ali Othman Z, Abu Bakar A, Syed Abdullah SM. Fuzzy-based shapelets for mining climate change time series patterns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9429. Springer Verlag. 2015. p. 38-50. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-25939-0_4
Al-Dharhani, Ghassan Saleh ; Ali Othman, Zulaiha ; Abu Bakar, Azuraliza ; Syed Abdullah, Sharifah Mastura. / Fuzzy-based shapelets for mining climate change time series patterns. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9429 Springer Verlag, 2015. pp. 38-50 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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