Fuzzy rules from ant-inspired computation

Qiang Shen, Michelle Galea

Research output: Contribution to conferencePaper

12 Citations (SciVal)
146 Downloads (Pure)

Abstract

A new approach to fuzzy rule induction from historical data is presented. The implemented system - FRANTIC - is a tested on a simple classification problem against a fuzzy tree induction algorithm, a genetic algorithm, and a numerical method for inducing fuzzy rules based on fuzzy subsethood values. The results obtained by FRANTIC indicate comparable or better classification accuracy, superior comprehensibility, and potentially more flexibility when applied to larger data sets. The impact of the knowledge representation used when generating fuzzy rules is also highlighted.
Original languageEnglish
Pages1691-1696
Number of pages6
Publication statusPublished - 2004

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