Association rule mining using time series data for Malaysia climate variability prediction

Rabiatul A.A. Rashid, Nohuddin Puteri Nor Ellyza, Zuraini Zainol

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

3 Citations (Scopus)

Abstract

Many studies have been conducted to determine how data mining can be used in predicting climate change. Previous studies showed many data mining methods have been used in related to climate prediction, however classification and clustering methods are widely used to generate the climate prediction model. In this study, Association Rule Mining (ARM) is used to discover hidden rules in time series climate data from previous years and to analyze the relationship between the discovered rules. The dataset used in this study is a set of weather data from the Petaling Jaya observation station in Selangor for the year 2013 to 2015. This paper aims to utilize ARM for extracting behavioural patterns within the climate data that can be used to develop the prediction model for climate variability. The proposed framework is developed to provide a better approach in understanding how ARM can be used to find meaningful patterns in the climate data and generate rules that can be used to build a prediction model.

Original languageEnglish
Title of host publicationAdvances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings
PublisherSpringer Verlag
Pages120-130
Number of pages11
Volume10645 LNCS
ISBN (Print)9783319700090
DOIs
Publication statusPublished - 1 Jan 2017
Event5th International Visual Informatics Conference, IVIC 2017 - Bangi, Malaysia
Duration: 28 Nov 201730 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10645 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Visual Informatics Conference, IVIC 2017
CountryMalaysia
CityBangi
Period28/11/1730/11/17

Fingerprint

Malaysia
Association Rule Mining
Association rules
Time Series Data
Climate
Time series
Prediction
Prediction Model
Data mining
Data Mining
Climate Models
Climate change
Climate Change
Clustering Methods
Weather

Keywords

  • Association rule mining
  • Climate prediction
  • Climate variability

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Rashid, R. A. A., Puteri Nor Ellyza, N., & Zainol, Z. (2017). Association rule mining using time series data for Malaysia climate variability prediction. In Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings (Vol. 10645 LNCS, pp. 120-130). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10645 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-70010-6_12

Association rule mining using time series data for Malaysia climate variability prediction. / Rashid, Rabiatul A.A.; Puteri Nor Ellyza, Nohuddin; Zainol, Zuraini.

Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. Vol. 10645 LNCS Springer Verlag, 2017. p. 120-130 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10645 LNCS).

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

Rashid, RAA, Puteri Nor Ellyza, N & Zainol, Z 2017, Association rule mining using time series data for Malaysia climate variability prediction. in Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. vol. 10645 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10645 LNCS, Springer Verlag, pp. 120-130, 5th International Visual Informatics Conference, IVIC 2017, Bangi, Malaysia, 28/11/17. https://doi.org/10.1007/978-3-319-70010-6_12
Rashid RAA, Puteri Nor Ellyza N, Zainol Z. Association rule mining using time series data for Malaysia climate variability prediction. In Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. Vol. 10645 LNCS. Springer Verlag. 2017. p. 120-130. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-70010-6_12
Rashid, Rabiatul A.A. ; Puteri Nor Ellyza, Nohuddin ; Zainol, Zuraini. / Association rule mining using time series data for Malaysia climate variability prediction. Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. Vol. 10645 LNCS Springer Verlag, 2017. pp. 120-130 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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