Imputation of missing microclimate data of coffee-pine agroforestry with machine learning

Imputation of missing microclimate data of coffee-pine agroforestry with machine learning

This research presents a comprehensive analysis of various imputation methods for addressing missing microclimate data in the context of coffee-pine agroforestry land in UB Forest. Utilizing Big data and Machine learning methods, the research evaluates the effectiveness of imputation missing microcl...

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Bibliographic Details
Main Authors: Heru Nurwarsito, Didik Suprayogo, Setyawan Purnomo Sakti, Cahyo Prayogo, Novanto Yudistira, Muhammad Rifqi Fauzi, Simon Oakley, Wayan Firdaus Mahmudy
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2024-02-01
Series:IJAIN (International Journal of Advances in Intelligent Informatics)
Subjects:
microclimate data
interpolation
shifted interpolation
k-nearest neighbors (knn)
linear regression
Online Access:http://ijain.org/index.php/IJAIN/article/view/1439

Internet

http://ijain.org/index.php/IJAIN/article/view/1439

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