Regional Typhoon Track Prediction Using Ensemble k-Nearest Neighbor Machine Learning in the GIS Environment

Regional Typhoon Track Prediction Using Ensemble k-Nearest Neighbor Machine Learning in the GIS Environment

This paper presents a novel approach for typhoon track prediction that potentially impacts a region using ensemble k-Nearest Neighbor (k-NN) in a GIS environment. In this work, the past typhoon tracks are zonally split into left and right classes by the current typhoon track and then grouped as an e...

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Bibliographic Details
Main Authors: Mamad Tamamadin, Changkye Lee, Seong-Hoon Kee, Jurng-Jae Yee
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Remote Sensing
Subjects:
k-Nearest Neighbor
GIS processing
machine learning
similarity
typhoon track prediction
Online Access:https://www.mdpi.com/2072-4292/14/21/5292

Internet

https://www.mdpi.com/2072-4292/14/21/5292

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