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Research on Fatigue Classification of Flight Simulation Training Cover

Research on Fatigue Classification of Flight Simulation Training

International Journal of Advanced Network, Monitoring and Controls
Volume 7 (2022): Issue 1 (January 2022)
By: Lien Wang and  Changyuan Wang  
Open Access
|May 2023
Figures & tables

Figures & Tables

Figure 1.

Simulated driving environment

Figure 2.

EEG acquisition equipment

Figure 3.

Accuracy of training set and test set

Figure 4.

Loss rate of training set and test set

图 1

模拟飞行环境

图 2

脑电设备

图 3

训练集和测试集的准确率

图 4

训练集和测试集的损失率

Experiment schedule

Participant ID001002003
Experiment 1019:00–9:3010:00–10:3011:00–11:30
Experiment 10213:30–14:0014:30–15:0015:30–16:00

实验计划表

Participant ID001002003
Experiment 1019:00–9:3010:00–10:3011:00–11:30
Experiment 10213:30–14:0014:30–15:0015:30–16:00
DOI: https://doi.org/10.2478/ijanmc-2022-0007 | Journal eISSN: 2470-8038
Journal RSS Feed
Language: English
Page range: 81 - 96
Published on: May 28, 2023
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Fatigue Classification,
Eeg,
Cnn,
Neural Network
Related subjects:
Computer sciences,
Computer sciences, other

© 2023 Lien Wang, Changyuan Wang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 7 (2022): Issue 1 (January 2022)
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