首页|New Findings in Support Vector Machines Described from Henan University of Techn ology (Gis-based Landslide Susceptibility Assessment Using Random Forest and Sup port Vector Machine Models: a Case Study of Chin State, Myanmar)
New Findings in Support Vector Machines Described from Henan University of Techn ology (Gis-based Landslide Susceptibility Assessment Using Random Forest and Sup port Vector Machine Models: a Case Study of Chin State, Myanmar)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Support Vecto r Machines have been published.According to news reporting originating in Henan , People’s Republic of China, by NewsRx journalists, research stated, “Chin Stat e in Myanmar experiences frequent landslides annually.This research aimed to co nstruct GISbased landslide susceptibility maps (LSMs) with two kinds of machine learning models, namely random forest (RF) and support vector machine (SVM).”
HenanPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector Machin esHenan University of Technology
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