Paper Info
Title
Multivariable Type-2 Self-Organizing Fuzzy Logic Controllers for Regulating Anesthesia with Rule Base Extraction
Abstract
In this paper, three different self-organizing fuzzy logic controllers (SOFLC), type-1, interval type-2 and zSlice general type-2 are used in the simulated control of anesthesia. Experimental results show that both the type-2 SOFLCs have better performance in comparison to the type-1 system. Based on the performance results, we then select the interval type-2 SOFLC to analyze rule usage during real-time regulation and control of anesthesia. Based on this we extracted a new reduced rule base which can provide a better basis to further research in understanding the SOFLC dynamic control behavior.
Year
DOI
Venue
2013
10.1109/.49
TAAI
Keywords
Field
DocType
rule base extraction,new reduced rule base,regulating anesthesia,rule usage,soflc dynamic control behavior,simulated control,better basis,performance result,logic controllers,multivariable type-2 self-organizing fuzzy,type-2 soflc,zslice general type-2,type-2 soflcs,better performance,fuzzy control
Neuro-fuzzy,Multivariable calculus,Multivariable control systems,Defuzzification,Fuzzy set operations,Control theory,Fuzzy logic,Anesthesia,Fuzzy control system,Mathematics
Conference
ISSN
Citations 
PageRank 
1066-6192
2
0.39
References 
Authors
5
5
Name
Order
Citations
PageRank
Yan-Xin Liu1192.23
Jiann Shing Shieh222428.44
Faiyaz Doctor345438.64
Shou-Zen Fan48211.48
Kuo-Kuang Jen5334.15