Python-and-MATLAB-RNN-LSTM-Model-for-Prediction-and-Forecast

RNN and LSTM models are programmed in Python and MATLAB for temperature forecasting. Data preprocessing, model training and evaluation.
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Mise à jour 29 juil. 2024

Intelligent Control Systems by Asst. Prof. Dr. Claudia F. Yaşar

This repository contains the curriculum materials used for the Intelligent Control Systems course YTU Department of Control and Automation Engineering.

Python-and-MATLAB-RNN-LSTM-Model-for-Prediction-and-Forecasting-Temperature

This work implements RNN and LSTM models using Python and MATLAB for temperature forecasting, covering setup, data preprocessing, model training, and evaluation with metrics like MAE and RMSE. It employs time series analysis and statistical assessment techniques, providing visualizations to demonstrate model accuracy and practical application.

Acknowledgements

I would like to express my gratitude to the students of the Intelligent Control Systems course of the YTÜ Control and Automation Engineering department, Class 2022 and 2023, whose dedication and hard work made this project possible. I am also deeply thankful to our Control Tech LAB team, Doctors Marco Rossi, and Melda Ulusoy for their invaluable contributions.

Citation pour cette source

Claudia Fernanda Yasar (2024). Python-and-MATLAB-RNN-LSTM-Model-for-Prediction-and-Forecast (https://github.com/ClaudiaYasar/Python-and-MATLAB-RNN-LSTM-Model-for-Prediction-and-Forecasting-Temperature), GitHub. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2022b
Compatible avec toutes les versions
Plateformes compatibles
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Version Publié le Notes de version
1.0.2

NA

1.0.1

update

1.0.0

Pour consulter ou signaler des problèmes liés à ce module complémentaire GitHub, accédez au dépôt GitHub.
Pour consulter ou signaler des problèmes liés à ce module complémentaire GitHub, accédez au dépôt GitHub.