التفاصيل البيبلوغرافية
| العنوان: |
Multidimensional data analysis software for fire hazard characteristics according to weather. |
| المؤلفون: |
Glagolev, Vladimir1 (AUTHOR) glagolev-jar@yandex.ru, Bazhenov, Ruslan1 (AUTHOR) r-i-bazhenov@yandex.ru, Dzhaparova, Saltanat2 (AUTHOR) saltanuraika@mail.ru, Gorbunova, Tatiana3 (AUTHOR) tngorbunova@yandex.ru, Dolmatova, Olga4 (AUTHOR) on.dolmatova@omgau.org, Arkhipova, Zoya5 (AUTHOR) zvarhipova@yandex.ru |
| المصدر: |
AIP Conference Proceedings. 2024, Vol. 3102 Issue 1, p1-5. 5p. |
| مصطلحات موضوعية: |
*FIRE risk assessment, *WILDFIRES, *DATA analysis, *DATABASE management, *ELECTRONIC data processing, *RANDOM forest algorithms |
| مصطلحات جغرافية: |
EAST Asia |
| مستخلص: |
MODIS remote monitoring software for fire hazard data analysis, depending on weather that uses meteorological data and information on vegetation fires, is within the research. The software is designed to calculate the meteorological fire danger index according to Nesterov, set up dependency relation of meteorological parameters (daytime air temperature and dew-point, daily precipitation) and vegetation fire propagation. The software involves a relational database model, MySQL database management server, HeidySQL service requesters called clients and Orange data processing. The software was verified in the Russian Far East throughout the fire-hazardous season of 2016. To evaluate fires included in Voronoy diagram, according to MSE, MAE, RMSE and R2, it was determined that Random Forest is the most helpful training algorithm. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
