<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

Evolutionary algorithms and fuzzy sets for discovering temporal rules

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

International Journal of Applied Mathematics and Computer Science

{"article-title":"Evolutionary algorithms and fuzzy sets for discovering temporal rules"}

A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal...

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Publié en ligne: 31 déc. 2013

Pages: 855 - 868

DOI: https://doi.org/10.2478/amcs-2013-0064

This content is open access.