vtech20/algerian-forest-fire-prediction

Forest fires are a major concern all over the world; each year, millions of hectares are lost. Algeria is one of the countries afflicted by this phenomena, which occurs primarily during the summer time. Forest fire detection and forecasting become critical issues for reducing the disaster's damage. Exploration of new fire detection and forecast systems as alternatives to existing ones becomes a necessity. The goal is to predict whether or not the fire will break out based on weather data. # algerian-forest-fire-prediction Forest fires are a major concern all over the world; each year, millions of hectares are lost. Algeria is one of the countries afflicted by this phenomena, which occurs primarily during the summer time. Forest fire detection and forecasting become critical issues for reducing the disaster's damage. Exploration of new fire detection and forecast systems as alternatives to existing ones becomes a necessity. The goal is to predict whether or not the fire will break out based on weather data. This application is built to predict the Fire break out based on the below fields: 1. Temp : temperature noon (temperature max) in Celsius degrees: 22 to 42 2. RH : Relative Humidity in %: 21 to 90 3. Ws :Wind speed in km/h: 6 to 29 4. Rain: total day in mm: 0 to 16.8 FWI Components 5. Fine Fuel Moisture Code (FFMC) index from the FWI system: 28.6 to 92.5 6. Duff Moisture Code (DMC) index from the FWI system: 1.1 to 65.9 7. Drought Code (DC) index from the FWI system: 7 to 220.4 8. Initial Spread Index (ISI) index from the FWI system: 0 to 18.5 9. Buildup Index (BUI) index from the FWI system: 1.1 to 68 10. Fire Weather Index (FWI) Index: 0 to 31.1