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Leveraging Artificial Intelligence for Cyanobacterial Bloom Prediction: A Hybrid Deep Learning and Generative Adversarial Network Framework for Accurate Forecasting and Proactive Management Cover

Leveraging Artificial Intelligence for Cyanobacterial Bloom Prediction: A Hybrid Deep Learning and Generative Adversarial Network Framework for Accurate Forecasting and Proactive Management

Foundations of Computing and Decision Sciences
Volume 50 (2025): Issue 4 (December 2025)
By: Nadjette Dendani,  Amel Saoudi,  Nour Djihane Amara,  Nabiha Azizi,  Julie Dugdale and  Rayenne Hadiby  
Open Access
|Dec 2025

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DOI: https://doi.org/10.2478/fcds-2025-0017 | Journal eISSN: 2300-3405 | Journal ISSN: 0867-6356
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Language: English
Page range: 427 - 450
Submitted on: Feb 25, 2025
Accepted on: Nov 5, 2025
Published on: Dec 8, 2025
Published by: Poznan University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
CyanoHABs,
Cyanotoxins,
Mexa Dam,
1D-CNN,
GANs,
LSTM,
R2,
RMSE
Related subjects:
Computer sciences,
Artificial intelligence,
Software development

© 2025 Nadjette Dendani, Amel Saoudi, Nour Djihane Amara, Nabiha Azizi, Julie Dugdale, Rayenne Hadiby, published by Poznan University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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