Abstract
A neural network modeling approach has been developed to analyze human pilots' control by utilizing the recorded time history of visual cues and pilot control inputs. An experimental method is developed to record the time histories of visual cues and pilot control inputs by analyzing recorded video data at a real flight. The developed method makes it possible to obtain neural network model of a pilot at a real landing case. In this research, the reliability of this method is confirmed by comparing the video data with GPS/INS data. The obtained results of the contribution ratios and sensitivities reveal the characteristics of the pilot's control.
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