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2013 | 23 | 4 | 855-868
Tytuł artykułu

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evolutionary algorithm combined with iterative rule learning to mine many rules. Temporal patterns are augmented into a dataset to analyse the method's ability in a controlled experiment. It is shown that the method is capable of discovering temporal patterns, and the effect of Boolean itemset support on the efficacy of discovering temporal fuzzy association rules is presented.
Rocznik
Tom
23
Numer
4
Strony
855-868
Opis fizyczny
Daty
wydano
2013
otrzymano
2012-02-13
poprawiono
2013-04-25
poprawiono
2013-07-17
Twórcy
  • Intelligent Systems Laboratory, Department of Engineering Mathematics, University of Bristol, Bristol, BS8 1UB, UK
  • Centre for Computational Intelligence, De Montfort University, The Gateway, Leicester, LE1 9BH, UK
  • Sheffield Business School, Sheffield Hallam University, Sheffield, S1 1WB, UK
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Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv23z4p855bwm
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