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See detailEvolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm
Matthews, Stephen G.; Gongora, Mario A.; Hopgood, Adrian ULg

in Lecture Notes in Artificial Intelligence (2011), 6678

A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal ... [more ▼]

A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. The novelty of this research lies in exploring the composition of quantitative and temporal fuzzy association rules and the approach of using a hybridisation of a multi-objective evolutionary algorithm with fuzzy sets. Results show the ability of a multi-objective evolutionary algorithm (NSGA-II) to evolve multiple target itemsets that have been augmented into synthetic datasets. [less ▲]

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See detailA Generalization of Semenov's Theorem to Automata over Real Numbers
Boigelot, Bernard ULg; Brusten, Julien ULg; Leroux, Jérôme

in Lecture Notes in Artificial Intelligence (2009), 5663

Detailed reference viewed: 89 (38 ULg)