Fire behavior prediction with artificial intelligence in thinned black pine (Pinus nigra Arnold) stand
Yazarlar (2)
Prof. Dr. Ömer KÜÇÜK Kastamonu Üniversitesi, Türkiye
Doç. Dr. Volkan Sevinç Muğla Sıtkı Koçman Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Forest Ecology and Management (Q1) | ||
| Dergi ISSN | 0378-1127 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 02-2023 |
| Cilt / Sayı / Sayfa | 529 / 1 / 120707–0 | DOI | 10.1016/j.foreco.2022.120707 |
| Makale Linki | http://dx.doi.org/10.1016/j.foreco.2022.120707 | ||
| UAK Araştırma Alanları |
Orman Entomolojisi ve Koruma
|
||
| Özet |
| Modeling forest fire behavior is very important for the effective control of forest fires and the setting up of necessary precautions before fires start. However, studies of forest fire behavior are complex studies that depend on many variables and usually involve large data sets. For this reason, the predictive power and speed of classical forecasting models are lower than of artificial intelligence models in cases involving big data and many variables. Moreover, classical forecasting models must satisfy certain statistical assumptions, unlike artificial intelligence methods. Thus, in this study, predictions were made of surface fire behavior, especially the rate of fire spread and the fire intensity, at the location at which fires started using two artificial intelligence methods, an artificial neural network and a decision tree. The accuracy of the developed models was fitted and tested. Finally, the classical regression model for … |
| Anahtar Kelimeler |
| Artificial intelligence | Artificial neural networks | Black pine | Decision trees | Fire behavior | Forest fires |
Science Direct
Fire behavior prediction with artificial intelligence in thinned black pine (Pinus nigra Arnold) stand
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 16 |
| Scopus | 18 |
| Google Scholar | 25 |