Improving the Forecast Accuracy of PM<sub>2.5</sub> Using SETAR-Tree Method: Case Study in Jakarta, Indonesia

Improving the Forecast Accuracy of PM<sub>2.5</sub> Using SETAR-Tree Method: Case Study in Jakarta, Indonesia

Air pollution in Jakarta, one of the most polluted cities globally, has reached critical levels, with PM<sub>2.5</sub> concentrations exceeding the WHO guidelines and posing significant health risks. Accurate forecasting of PM<sub>2.5</sub> is crucial for effective air qualit...

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Bibliographic Details
Main Authors: Dinda Ayu Safira, Heri Kuswanto, Muhammad Ahsan
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Atmosphere
Subjects:
SETAR-Tree
LSTM
PM<sub>2.5</sub>
air pollution
forecasting
nonlinear time series
Online Access:https://www.mdpi.com/2073-4433/16/1/23
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