The aim is to predict the burned area of forest fires, in the northeast region of Portugal, by using meteorological and other data
Format
A data frame with 517 observations on the following 13 variables.
X
x-axis spatial coordinate within the Montesinho park map: 1 to 9
Y
y-axis spatial coordinate within the Montesinho park map: 2 to 9
month
month of the year: "jan" to "dec"
day
day of the week: "mon" to "sun"
FFMC
FFMC index from the FWI system: 18.7 to 96.20
DMC
DMC index from the FWI system: 1.1 to 291.3
DC
DC index from the FWI system: 7.9 to 860.6
ISI
ISI index from the FWI system: 0.0 to 56.10
temp
temperature in Celsius degrees: 2.2 to 33.30
RH
relative humidity in %: 15.0 to 100
wind
wind speed in km/h: 0.40 to 9.40
rain
outside rain in mm/m2 : 0.0 to 6.4
area
the burned area of the forest (in ha): 0.00 to 1090.84#'
Source
Paulo Cortez, pcortez '@' dsi.uminho.pt, Department of Information Systems, University of Minho, Portugal. Aníbal Morais, araimorais '@' gmail.com, Department of Information Systems, University of Minho, Portugal.
References
P. Cortez and A. Morais. A Data Mining Approach to Predict Forest Fires using Meteorological Data. In J. Neves, M. F. Santos and J. Machado Eds., New Trends in Artificial Intelligence, Proceedings of the 13th EPIA 2007 - Portuguese Conference on Artificial Intelligence, December, Guimarães, Portugal, pp. 512-523, 2007. APPIA, ISBN-13 978-989-95618-0-9 https://archive.ics.uci.edu/ml/machine-learning-databases/forest-fires/forestfires.csv https://archive.ics.uci.edu/ml/datasets/Forest+Fires