Prediction of landing speed of aircraft based on AE-ANFIS

H.X. Yang; X.H. Xu; X.P. Cui; J.J. Huang

doi:10.1117/12.2655818

12 January 2023 Prediction of landing speed of aircraft based on AE-ANFIS

H.X. Yang, X.H. Xu, X.P. Cui, J.J. Huang

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 125090E (2023) https://doi.org/10.1117/12.2655818
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

Aiming at the problem that the advanced arresting device is difficult to obtain the landing speed of the aircraft in real time, this paper predicts the speed of the aircraft through the self-encoding fuzzy inference system (AE-ANFIS). Firstly, the working principle of the advanced arresting system is expounded, and the sensors directly related to the aircraft speed measurement are analyzed. And filter auxiliary variables through feature extraction and maximum information coefficient (MIC); then predict acceleration through adaptive fuzzy neural network (ANFIS); finally, for the problem of over-fitting caused by the large number of ANFIS rules, an auto-encoder (AE) method is proposed. Data dimensionality reduction is performed by extracting abstract features, which effectively improves the prediction accuracy of ANFIS. The experimental results show that the method proposed in this paper can fit the aircraft speed well, and the accuracy is better than traditional ANFIS and BP, LSTM, GoogleNet, AlexNet and other algorithms.

Citation Download Citation

H.X. Yang, X.H. Xu, X.P. Cui, and J.J. Huang "Prediction of landing speed of aircraft based on AE-ANFIS", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 125090E (12 January 2023); https://doi.org/10.1117/12.2655818

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