Abstract
Autonomous temporal linguistic rule extraction is an application of growing interest for its relevance to both decision support systems and fuzzy controllers. In the presented work, rules are evaluated using three qualitative metrics based on their representation on the truth space diagram. Each metric is then treated as a conflicting optimization goal and multiple objective evolutionary algorithm is used to obtain a set of optimal non-dominant rules. Novel techniques for data pre-processing and rule set post-processing are designed. Data collected from a simulated hot and cold water mixer is used to validate the proposed procedure.
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