INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
PREDICTING FOREST FIRES WITH DIFFERENT DATA MINING TECHNIQUES
Authors Name:
Madhurima De
, Linika Labdhi , Bindu Garg
Unique Id:
IJSDR2004068
Published In:
Volume 5 Issue 4, April-2020
Abstract:
Forest fires are one of the most frequently occurring disasters in recent years. The behaviour of forest fire and its severity result from a combination of factors such as available fuels, physical setting, and weather. Analysis of historical meteorological data and national fire records in western North America show the primacy of climate in driving large regional fires via wet periods that create substantial fuels, or drought and warming that extend conducive fire weather. The effects of forest fires creates a very lasting impact on the environment as it leads to deforestation and global warming, which is also one of its major cause of occurrence. Forest fires are dealt by collecting the satellite images of forest and if there is any emergency caused by the fires then the authorities are notified to mitigate its effects. In this work, we will be exploring various Data Mining (DM) approaches to predict the burnt area of forest fires. Five different DM techniques, e.g. Support Vector Machines (SVM) and Random Forests, and four distinct feature selection setups (using spatial, temporal, FWI components and weather attributes), were tested on recent real-world data.
Keywords:
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Cite Article:
"PREDICTING FOREST FIRES WITH DIFFERENT DATA MINING TECHNIQUES", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 4, page no.382 - 386, April-2020, Available :http://www.ijsdr.org/papers/IJSDR2004068.pdf
Downloads:
000337357
Publication Details:
Published Paper ID: IJSDR2004068
Registration ID:191634
Published In: Volume 5 Issue 4, April-2020
DOI (Digital Object Identifier):
Page No: 382 - 386
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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