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This project is made to predict the Algerian Forest Fires.

Algerian Forest Fires Dataset

Data Set Information:

The dataset includes 244 instances that regroup a data of two regions of Algeria,namely the Bejaia region located in the northeast of Algeria and the Sidi Bel-abbes region located in the northwest of Algeria.

122 instances for each region.

The period from June 2012 to September 2012. The dataset includes 11 attribues and 1 output attribue (class) The 244 instances have been classified into fire(138 classes) and not fire (106 classes) classes.

Attribute Information:

  1. Date : (DD/MM/YYYY) Day, month ('june' to 'september'), year (2012) Weather data observations
  2. Temp : temperature noon (temperature max) in Celsius degrees: 22 to 42
  3. RH : Relative Humidity in %: 21 to 90
  4. Ws :Wind speed in km/h: 6 to 29
  5. Rain: total day in mm: 0 to 16.8 FWI Components
  6. Fine Fuel Moisture Code (FFMC) index from the FWI system: 28.6 to 92.5
  7. Duff Moisture Code (DMC) index from the FWI system: 1.1 to 65.9
  8. Drought Code (DC) index from the FWI system: 7 to 220.4
  9. Initial Spread Index (ISI) index from the FWI system: 0 to 18.5
  10. Buildup Index (BUI) index from the FWI system: 1.1 to 68
  11. Fire Weather Index (FWI) Index: 0 to 31.1
  12. Classes: two classes, namely Fire and not Fire

FLOW OF THE PROJECT :

  • Data collection for the Algerian Forest Fires.
  • EDA on the Algerian Forest Fires Dataset.
  • FE on the Algerian Forest Fires Dataset.
  • Model training by using the Ridge Regression with an accuracy of 98.4%.
  • Web Application Design by using the FLASK.
  • Deployment of the Model on the AWS with Elastic Beanstalk and CodePipeline services.