Özet
This study aimed to identify the method of using artificial intelligence and machine learning to protect people from the effects of natural disaster risks, The descriptive approach was followed to achieve this goal. The data (from international Bank’s data, and of Global Facility for Disaster Reduction and Recovery’ data), were collected to collect the necessary information and statistics. This research revealed through case studies that the machine learning for disaster risks management often applied to methods used in the classification of remotely sensed satellites, and from seismic sensor data networks and building inspection records to social media posts. Research has also shown that careful identification of vulnerability is one of the foundations for more effective risk management, And that the use of machine learning algorithms can significantly reduce the costs of natural disaster risk management.
Abstract
This study aimed to identify the method of using artificial intelligence and machine learning to protect people from the effects of natural disaster risks, The descriptive approach was followed to achieve this goal. The data (from international Bank’s data, and of Global Facility for Disaster Reduction and Recovery’ data), were collected to collect the necessary information and statistics. This research revealed through case studies that the machine learning for disaster risks management often applied to methods used in the classification of remotely sensed satellites, and from seismic sensor data networks and building inspection records to social media posts. Research has also shown that careful identification of vulnerability is one of the foundations for more effective risk management, And that the use of machine learning algorithms can significantly reduce the costs of natural disaster risk management.
Yazarlar
Imane BOUGUERRA, & Hadj Moussa MANSOURI, & Hadj Moussa MANSOURI, & Hadj Moussa MANSOURI
Anahtar Kelimeler
Artificial Intelligence, Machine Learning, Risks, Natural Disaster Management.
Yayın Bilgileri
- Cilt
- 7
- Sayı
- 53
- Yıl
- 2020
- Dil
- Türkçe
- Durum
- Yayınlandı
- Görüntülenme
- 0
- İndirme
- 0
Dosyalar
Atıf ve İndeksleme Bilgileri
Bu bilgiler akademik indeksler, atıf yöneticileri ve sosyal medya paylaşım araçları için hazırlanmıştır.
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