Performance of machine learning models to forecast PM10 levels

Performance of machine learning models to forecast PM10 levels

Machine learning techniques have garnered considerable attention in modern technologies due to their promising outcomes across various domains. This paper presents the comprehensive methodology of an optimized and efficient forecasting approach for Particulate Matter 10, specifically tailored to pre...

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Bibliographic Details
Main Authors: Lakindu Mampitiya, Namal Rathnayake, Yukinobu Hoshino, Upaka Rathnayake
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:MethodsX
Subjects:
Ensemble Model, XGBoost, CatBoost, LightGBM, LSTM, Bi-LSTM, GRU, ANN
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016124000128

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http://www.sciencedirect.com/science/article/pii/S2215016124000128

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