Multiple objective evolutionary algorithm for temporal linguistic rule extraction.
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. Performance metrics are then treated as competing objectives and the multiple objective evolutionary algorithm is used to search for an optimal set of nondominant rules. Novel techniques for data pre-processing and rule set post-processing are designed that deal directly with the delays involved in dynamic systems. Data collected from a simulated hot and cold water mixer are used to validate the proposed procedure.
DeLima
Pedro G
PG
School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK 74078-5032, USA.
Yen
Gary G
GG
D000465:Algorithms; D001185:Artificial Intelligence; D003661:Decision Support Techniques; D016247:Information Storage and Retrieval / Q000379:methods*; D008037:Linguistics; D016015:Logistic Models; D013997:Time Factors