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Paper Abstract and Keywords
Presentation 2024-01-25 16:40
[Poster Presentation] Dust Forecasting using ARIMA and ARIMAX Models
Nuntouchaporn Prateepausanont (College of digital science, Prince of Songkla Univ.), Anny Mardjo (Prince of Songkla Univ. , Trang Campus), Chidchanok Choksuchat, Korakot Wichitsa-nguan Jetwanna, Thanathip Limna (Prince of Songkla Univ.) IA2023-69
Abstract (in Japanese) (See Japanese page) 
(in English) Southern Thailand faces air pollution problems from transboundary haze, as shown in the Pollution Control Department, caused by dust particles moving from areas within Indonesia. This haze affects the health of the population in the southern region over a wide area. Therefore, predicting the amount of dust that will cover the area would enable us to promptly propose solutions to reduce the impact of dust. the environmental science and internet architecture/applications can intersect in various ways, particularly concerning data collection, data sharing, sustainability, and the application of internet technologies for environmental monitoring and research. Collaboration between experts from both fields can lead to innovative solutions for addressing environmental challenges and reducing the environmental footprint of internet technologies. This research presents dust forecasting in Southern Thailand by considering the utilization of ARIMA for univariate time series forecasting, ARIMAX for multivariate time series forecasting with exogenous variables. The study uses dataset that generated from the RCNAME for the years spanning from January 2016 to December 2022. The remote sensors, including PCD and TMD, were collected concurrently with the laboratory data. The research methodology consists of data cleansing, exploratory data analysis, and fitting time-series models. Finally, the ARIMA (0,1,1) model offered the highest performance model for forecasting due to the lowest MAE (=1.6857), MAPE (=3.76126) and RMSE (=0.2304), while the ARIMAX (0,1,2) model has a lower MAE (=1.6857), MAPE (=27.30) and RMSE (=2.2937). The highest performance model for forecasting is the ARIMA (0,1,1) model.
Keyword (in Japanese) (See Japanese page) 
(in English) PM / ARIMA / ARIMAX / Forecasting / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 372, IA2023-69, pp. 52-57, Jan. 2024.
Paper # IA2023-69 
Date of Issue 2024-01-18 (IA) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee IA  
Conference Date 2024-01-25 - 2024-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Kwansei Gakuin Univiversity, Marunouchi Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Sensor Network, IoT, M2M, etc., and IA2023 - Workshop on Internet Architecture and Applications 2023 
Paper Information
Registration To IA 
Conference Code 2024-01-IA 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dust Forecasting using ARIMA and ARIMAX Models 
Sub Title (in English)  
Keyword(1) PM  
Keyword(2) ARIMA  
Keyword(3) ARIMAX  
Keyword(4) Forecasting  
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Keyword(6)  
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1st Author's Name Nuntouchaporn Prateepausanont  
1st Author's Affiliation College of digital science, Prince of Songkla University (College of digital science, Prince of Songkla Univ.)
2nd Author's Name Anny Mardjo  
2nd Author's Affiliation Prince of Songkla University, Trang Campus (Prince of Songkla Univ. , Trang Campus)
3rd Author's Name Chidchanok Choksuchat  
3rd Author's Affiliation Prince of Songkla University (Prince of Songkla Univ.)
4th Author's Name Korakot Wichitsa-nguan Jetwanna  
4th Author's Affiliation Prince of Songkla University (Prince of Songkla Univ.)
5th Author's Name Thanathip Limna  
5th Author's Affiliation Prince of Songkla University (Prince of Songkla Univ.)
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Speaker Author-1 
Date Time 2024-01-25 16:40:00 
Presentation Time 30 minutes 
Registration for IA 
Paper # IA2023-69 
Volume (vol) vol.123 
Number (no) no.372 
Page pp.52-57 
#Pages 6 
Date of Issue 2024-01-18 (IA) 

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