Comparative study on machine learning algorithms for early fire forest detection system using geodata
| Main Authors: | Zouiten Mohammed, Chaaouan Hanae, Setti Larbi |
|---|---|
| Format: | Article eJournal |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4136970 |
Daftar Isi:
- Forest fires have become a great risk for countries. To minimize their impact and prevent this phenomenon, scientific methods have emerged. Notably machine learning algorithms and decision-making Geographical Information Systems. Therefore, a competitive spatial prediction model for early fire forest detection system using geodata can be proposed. This model can help researchers to predict forest fires and identify risk zonas. System using machine learning algorithm on geodata will be able to notify in real time the interested parts and authorities by providing alerts and presenting on maps based on geographical treatments for more efficacity and analyzing of the situation. This research extends the application of machine learning algorithms for early fire forest prediction to detection and representation in geographical information system (GIS) maps.