This paper presents an overview of the key points that help to build a system for detecting and analyzing afterwards the climate change in the Maghreb region. Our main goal is to propose a design and an implementation of a meteorology data warehouse built from multiple sources and intended to end-users for making prediction and effective decision. More precisely, a digital system involving a clean, complete and consistent store of all gathered data is developed. Such repository is accompanied of data warehousing and mining tools enabling improvement of climate prediction, statistical analysis, climatic classification and clustering, frequent pattern extraction and association rule mining. Unlike previous efforts, the most important purpose of this study is to observe the climate change in Maghreb region and for the long-term the ability to predict natural disasters such as severe floods and droughts.

Drias, Y., Drias, H., Khennak, I. (2022). Data Warehousing and Mining for Climate Change: Application to the Maghreb Region. In Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) (pp.293-302). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-96302-6_27].

Data Warehousing and Mining for Climate Change: Application to the Maghreb Region

Drias Y.
;
2022

Abstract

This paper presents an overview of the key points that help to build a system for detecting and analyzing afterwards the climate change in the Maghreb region. Our main goal is to propose a design and an implementation of a meteorology data warehouse built from multiple sources and intended to end-users for making prediction and effective decision. More precisely, a digital system involving a clean, complete and consistent store of all gathered data is developed. Such repository is accompanied of data warehousing and mining tools enabling improvement of climate prediction, statistical analysis, climatic classification and clustering, frequent pattern extraction and association rule mining. Unlike previous efforts, the most important purpose of this study is to observe the climate change in Maghreb region and for the long-term the ability to predict natural disasters such as severe floods and droughts.
paper
Climate change; Data mining; Data warehouse; Maghreb region; Predictions;
English
13th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2021 and 13th World Congress on Nature and Biologically Inspired Computing, NaBIC 2021 - 15 December 2021 through 17 December 2021
2021
Ajith Abraham, Andries Engelbrecht, Fabio Scotti, Niketa Gandhi, Pooja Manghirmalani Mishra, Giancarlo Fortino, Virgilijus Sakalauskas, Sabri Pllana
Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)
9783030963019
2022
417 LNNS
293
302
none
Drias, Y., Drias, H., Khennak, I. (2022). Data Warehousing and Mining for Climate Change: Application to the Maghreb Region. In Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) (pp.293-302). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-96302-6_27].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/506750
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