Forest Fire Prediction using Machine Learning Models based on DC, Wind and RH
Tanishka Jain1, Nayan Sharma2
1Tanishka Jain, Department of Computer Science & Engineering, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
2Nayan Sharma, Department of Computer Science & Engineering, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
Manuscript received on 24 February 2020 | Revised Manuscript received on 10 March 2020 | Manuscript Published on 18 March 2020 | PP: 142-143 | Volume-8 Issue-6S March 2020 | Retrieval Number: F10260386S20/2020©BEIESP | DOI: 10.35940/ijrte.F1026.0386S20
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The paper points out forest fire prediction using machine learning models on the basis of viz. DC, Wind, RH out of the several machine learning classifier algorithms, It is relevant that random forest algorithm generates optimum accuracy (99.61%).
Keywords: Forest Fire, Machine Learning, DC, Wind, RH.
Scope of the Article: Machine Learning