Grande, Paoloemilio (A.A. 2024/2025) AI for climate change: unlocking the potential of time series for a safer future. Tesi di Laurea in Machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 70. [Master's Degree Thesis]

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Abstract/Index

State of the art and research gaps. Literature review and background. Climate change: theory and dynamics. From global observation to local observation: case studies and reference research. Theoretical foundations of machine learning for time series. Fundamental concepts and statistical aspects. Machine learning architectures for time series forecasting. Evaluation metrics for time series forecasting. Unveiling local climate dynamics: a multiscale station-based study. Data acquisition and preprocessing. Methodological framework and models implementation. Discussion.

References

Bibliografia: pp. 67-70.

Thesis Type:	Master's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91)
Chair:	Machine learning
Thesis Supervisor:	Italiano, Giuseppe Francesco
Thesis Co-Supervisor:	Sinaimeri, Blerina
Academic Year:	2024/2025
Session:	Summer
Deposited by:	Alessandro Perfetti
Date Deposited:	05 Nov 2025 11:42
Last Modified:	05 Nov 2025 11:42
URI:	https://tesi.luiss.it/id/eprint/43632

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