Enhancing flood-prone area mapping: fine-tuning the K-nearest neighbors (KNN) algorithm for spatial modelling

Enhancing flood-prone area mapping: fine-tuning the K-nearest neighbors (KNN) algorithm for spatial modelling

ABSTRACTThis study focuses on determining the optimal distance metric in the K-Nearest Neighbors (KNN) algorithm for spatial modelling of floods. Four distance metrics of the KNN algorithm, namely KNN-Manhattan, KNN-Minkowski, KNN-Euclidean, and KNN-Chebyshev, were utilized for flood susceptibility...

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Bibliographic Details
Main Authors: Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Saman Razavi, Soo-Mi Choi
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:International Journal of Digital Earth
Subjects:
Flood-prone areas
optimal machine learning
remote sensing
spatial modelling
metaheuristic algorithms
Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2024.2311325

Internet

https://www.tandfonline.com/doi/10.1080/17538947.2024.2311325

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