Paper Info
Title
Adaptive Fuzzy Approaches To Modelling Operator Functional States In A Human-Machine Process Control System
Abstract
This paper assesses the operator functional state (OFS) of human operators based on a collection of psychophysiological and performance measures. Two types of adaptive fuzzy models, namely ANFIS (adaptive-network-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved in an automation-enhanced cabin air management system (aCAMS). The adaptive fuzzy modelling procedures are described and then validated using real-life data measured from such a simulated human-machine process control system.
Year
DOI
Venue
2007
10.1109/FUZZY.2007.4295371
2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4
Keywords
Field
DocType
management system,fuzzy set theory,human computer interaction,fuzzy systems,genetic algorithm,fuzzy control,adaptive control,fuzzy sets,process control system,process control,psychology,genetic algorithms
Neuro-fuzzy,Fuzzy classification,Computer science,Fuzzy set operations,Fuzzy logic,Fuzzy set,Artificial intelligence,Adaptive neuro fuzzy inference system,Adaptive control,Fuzzy control system,Machine learning
Conference
ISSN
Citations 
PageRank 
1098-7584
3
0.61
References 
Authors
1
7
Name
Order
Citations
PageRank
Mahdi Mahfouf123533.17
Jian-hua Zhang230.61
Derek A. Linkens321525.36
A. M. A. Nassef430.95
Peter Nickel530.61
G. Hockey69721.07
Andrew C. Roberts730.61