Autor:

Matthews, Stephen G. ; Gongora, Mario A. ; Hopgood, Adrian A.

Współtwórca:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Tytuł:

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Tytuł publikacji grupowej:

AMCS, Volume 23 (2013)

Temat i słowa kluczowe:

fuzzy association rules ; temporal association rules ; multi-objective evolutionary algorithm

Abstract:

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.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2013

Typ zasobu:

artykuł

DOI:

10.2478/amcs-2013-0064

Strony:

855-868

Źródło:

AMCS, volume 23, number 4 (2013) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego