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OneDrive_1_18-09-2023.zip (59.87 MB)

Code and data supporting 'A Comprehensive Analysis of Machine Learning and Deep Learning Models for Identifying Pilots' Mental States from Imbalanced Physiological Data'

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posted on 2023-09-18, 15:40 authored by Ibrahim Alreshidi, Irene MoulitsasIrene Moulitsas, Karl JenkinsKarl Jenkins, Satendra Yadav

Data: 

This folder contains:

- A dataset called combined_df4, which contains the power spectral density features after employing SMOTE.

- A dataset called combined_df5, which contains the power spectral density features after employing SMOTE and cosine similarity.

Source code:

This folder contains:

- A jupyter notebook called AdaBoost.ipynb which was used to generate the results for the AdaBoost algorithm.

- A jupyter notebook called CNN.ipynb which was used to generate the results for the CNN algorithm.

- A jupyter notebook called CNN+LSTM.ipynb which was used to generate the results for the CNN+LSTMalgorithm.

- A jupyter notebook called LSTM.ipynb which was used to generate the results for the LSTMalgorithm.

- A jupyter notebook called FNN.ipynb which was used to generate the results for the FNN algorithm.

- A jupyter notebook called Random_Forest.ipynb which was used to generate the results for the Random Forest algorithm.

- A jupyter notebook called XGBoost.ipynb which was used to generate the results for the XGBoost algorithm.

History

Authoriser (e.g. PI/supervisor)

i.moulitsas@cranfield.ac.uk

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