Forecasting PM2.5 in Malaysia Using a Hybrid Model

Forecasting PM2.5 in Malaysia Using a Hybrid Model

Abstract Predicting future PM2.5 concentrations based on knowledge obtained from past observational data is very useful for predicting air pollution. This paper aims to develop a hybrid forecasting model using an Artificial Neural Network (ANN) and Triple Exponential Smoothing (TES) on clustered PM2...

Full description

Saved in:
Bibliographic Details
Main Authors: Ezahtulsyahreen Ab. Rahman, Firdaus Mohamad Hamzah, Mohd Talib Latif, Azman Azid
Format: Article
Language:English
Published: Springer 2023-06-01
Series:Aerosol and Air Quality Research
Subjects:
PM2.5
Artificial neural network
Exponential smoothing
Hybrid model
Online Access:https://doi.org/10.4209/aaqr.230006
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.4209/aaqr.230006

Similar Items