Title :
An improved fuzzy modeling algorithm. II. System identification
Author :
Emami, Mohammad R. ; Turksen, I. Burhan ; Goldenberg, Andrew A.
Author_Institution :
Robotics & Autom. Lab., Toronto Univ., Ont., Canada
Abstract :
For pt.I see ibid. In this part we focus on the fuzzy system identification stage. The Fuzzy C-Means (FCM) clustering algorithm is investigated. Two indices are introduced for assignment of number of rules and level of “fuzziness”. An efficient method is also suggested for choosing the initial location of cluster centers. The classification problem is addressed in fuzzy modeling; and an efficient strategy is proposed for assignment of dominant input variables and their membership functions
Keywords :
fuzzy control; fuzzy set theory; fuzzy systems; identification; inference mechanisms; pattern classification; uncertainty handling; classification problem; cluster centers; dominant input variables; fuzziness; fuzzy C-means clustering algorithm; fuzzy modeling; fuzzy modeling algorithm; membership functions; system identification; Clustering algorithms; Flowcharts; Fuzzy systems; Input variables; Intelligent robots; Intelligent systems; Laboratories; Parameter estimation; Robotics and automation; System identification;
Conference_Titel :
Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American
Conference_Location :
Berkeley, CA
Print_ISBN :
0-7803-3225-3
DOI :
10.1109/NAFIPS.1996.534748
