Download PDFOpen PDF in browser

A Comprehensive Review on Prediction and Detection of Forest Fires Using Machine Learning Algorithms

EasyChair Preprint no. 6334

23 pagesDate: August 22, 2021

Abstract

Forests play a very important role in sustaining the environment. Wildfires or forest fires are not only responsible for the destruction of the natural environment, but also affects the ecological balance. A large number of fires are considered under man made causes and climate change. Although other factors like drought, wind, topography, plants, etc., have an important influence on fire appearance and its spreading. The prediction and detection of fire movement is important for fire prevention, organization of preventive measures and optimal storage of firefighting resources. An important tool for the prediction and detection of forest fires is modeling the relations between the fire threat and the influence factors and it can be done with the help of Data Mining and the Algorithms. Data mining is extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases. It is also known as knowledge discovery in databases (KDD). The knowledge discovered from the data by applying various supervised, unsupervised and semi-supervised algorithms helps in predicting the outcomes and taking decisions. In the current study the comprehensive review of the research done by different reviewers is done and analyzed the most common factors which cannot remain constant throughout the year and their change is one of the key factors for the forest fires. These factors are temperature, relative humidity, precipitation, wind speed, month, heat, smoke and atmospheric gases. The has reviewed different supervised, unsupervised and semi-supervised algorithms applied for prediction of forest fire.

Keyphrases: Algorithms, Data Mining, forest fire, machine learning, semi-supervised, supervised, unsupervised

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:6334,
  author = {Anshul Hooda and Antara Asthana and Dr.Vidya Patkar},
  title = {A Comprehensive Review on Prediction and Detection of Forest Fires Using Machine Learning Algorithms},
  howpublished = {EasyChair Preprint no. 6334},

  year = {EasyChair, 2021}}
Download PDFOpen PDF in browser