| Titre : | Using machine learning techniques and reconnaissance drought index for meteorological drought forecasting |
| Auteurs : | Mohamed Ammour, Auteur ; Hamza Bouguerra, Directeur de thèse ; Salim Benziada, Directeur de thèse |
| Type de document : | document électronique |
| Editeur : | [S.l.] : [s.n.], 2024 |
| Format : | 1 fichier PDF (9.7 Mo) |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet. Mémoire de Projet de Fin d’Études : Hydraulique : Alger, École Nationale Polytechnique : 2024 Bibliogr. p. 101-111 |
| Langues : | Anglais |
| Index. décimale : | PH00924 |
| Tags : | Drought Drought forecasting Reconnaissance drought index Atmospheric circulation indices Agriculture |
| Résumé : |
Climate change significantly impacts our environment, leading to increase drought, more frequent wildfires, and unpredictable rainfall patterns. These changes disrupt ecosystems and human livelihoods, highlighting the urgent need for climate action. Understanding these effects is crucial for developing effective mitigation and adaptation strategies. In our project, we focus specifically on the issue of drought in Algeria and its profound effects on agriculture. Therefore, the objective of this project is the development of a forecasting model to address the need for an early warning system against drought in Algeria. Utilizing the approach of linking between atmospheric circulation indices and drought indices, the reconnaissance drought index in our case, in the northwest region of Algeria. This work not only addresses immediate safety concerns but also lays the groundwork for various perspectives, potentially contributing to advancements in drought mitigations. |
Exemplaires (1)
| Cote | Support | Localisation | Section | Disponibilité | Spécialité | Etat_Exemplaire |
|---|---|---|---|---|---|---|
| PH00924 | Ressources électroniques | Bibliothèque centrale | Projet Fin d'Etudes | Disponible | Hydraulique | Téléchargeable |
Documents numériques (1)
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AMMOUR.Mohamed.pdf URL
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