Title :
GENIE: a general neurofuzzy inference environment
Author :
Zhang, Z.W. ; Anderson, P. ; Bignall, B.
Author_Institution :
Gippsland Sch. of Comput. & Inf. Technol., Monash Univ., Clayton, Vic., Australia
Abstract :
As the application domain of neuro-fuzzy inferencing systems becomes broader, users will find increasing difficulty in selecting the right models for their specific application. This paper describes the design and implementation of a general neuro-fuzzy inference environment (GENIE). Its purpose is to facilitate the assessment of new learning strategies and control models. GENIE includes a number of well known neuro-fuzzy inference (NFI) systems. Besides its control, GENIE gives users a graphical display of membership functions and the system being controlled, thereby allowing users to visually monitor the changes occurring inside the controller and the system being controlled. Two new performance metrics for neuro-fuzzy controllers are described that have been incorporated into GENIE
Keywords :
fuzzy control; fuzzy neural nets; inference mechanisms; learning (artificial intelligence); neurocontrollers; uncertainty handling; GENIE; backpropagation; control models; graphical display; learning strategies; membership functions; model selection; neurofuzzy control; neurofuzzy inference environment; performance metrics; reinforcement learning; system design; system implementation; Control systems; Displays; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Information technology; Learning; Measurement; Monitoring; Neural networks;
Conference_Titel :
Fuzzy Systems Symposium, 1996. Soft Computing in Intelligent Systems and Information Processing., Proceedings of the 1996 Asian
Conference_Location :
Kenting
Print_ISBN :
0-7803-3687-9
DOI :
10.1109/AFSS.1996.583598
