Electronics Optics & Control, Volume. 25, Issue 4, 78(2018)
Flight Performance Prediction Based on BFA-GRNN Network
The prediction of flight performance via the analysis of pilots, multiple physiological signals is one of the most noteworthy issues in the area of aviation safety. A flight performance prediction model using Bacterial Foraging Algorithm (BFA) to optimize Generalized Regression Neural Network (GRNN) is proposed to train the pilots, multiple physiological signals, so as to predict the flight performance in simulated flight tests. Through the comparison between the predicted results of the model and the real value of the flight performance, the validity of the proposed method is proved, which provides a new approach to the prediction of flight performance.
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LIU Wenmeng, QIAN Chen, HUANG Dan. Flight Performance Prediction Based on BFA-GRNN Network[J]. Electronics Optics & Control, 2018, 25(4): 78
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Received: Jun. 5, 2017
Accepted: --
Published Online: Jan. 21, 2021
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