Robotics & Machine Learning Daily News2024,Issue(Dec.18) :121-121.

Reports Summarize Machine Learning Research from University of Tehran (Evaluatin g the Impact of Recursive Feature Elimination on Machine Learning Models for Pre dicting Forest Fire-Prone Zones)

Robotics & Machine Learning Daily News2024,Issue(Dec.18) :121-121.

Reports Summarize Machine Learning Research from University of Tehran (Evaluatin g the Impact of Recursive Feature Elimination on Machine Learning Models for Pre dicting Forest Fire-Prone Zones)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New study results on artificial intell igence have been published. According to newsreporting originating from Tehran, Iran, by NewsRx correspondents, research stated, “This study aimedto enhance t he accuracy of forest fire susceptibility mapping (FSM) by innovatively applying recursivefeature elimination (RFE) with an ensemble of machine learning models , specifically Support VectorMachine (SVM) and Random Forest (RF), to identify key fire factors. The fire zones were derived fromMODIS satellite imagery from 2012 to 2017.”

Key words

University of Tehran/Tehran/Iran/Asia/Cyborgs/Emerging Technologies/Machine Learning/Support Vector Machines

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文