J. Zhang, M. Mahfouf, D.A. Linkens, P. Nickel, G.R.J. Hockey, and A.C. Roberts (UK)
OFS, fuzzy system, genetic algorithm
This paper assesses the operator functional state (OFS) based on a collection of psychophysiological (i.e., cardiovascular and EEG) and performance measures. Two types of adaptive fuzzy model, 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 fuzzy modelling procedures are described in detail. The adaptive fuzzy models are validated using real-life data measured from two well-trained collegiate participants. The preliminary simulation results implied that the overall performance of human-machine system may be improved by identifying and predicting OFSs via the proposed fuzzy models.
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