A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area

© 2016 The Authors. Most of time series model are usually investigated and implemented by ARIMA and Neural Networks (NNs) model. However, ARIMA model may not be adequate for complex patterned problem while NNs model can well reveal the correlation of nonlinear pattern. Since, over-fitting due to a l...

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Main Authors:	Rati Wongsathan, Isaravuth Seedadan
Format:	Conference Proceeding
Published:	2018
Subjects:	Computer Science
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84999633655&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55547
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Institution:	Chiang Mai University

id	th-cmuir.6653943832-55547
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spelling	th-cmuir.6653943832-555472018-09-05T02:57:46Z A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area Rati Wongsathan Isaravuth Seedadan Computer Science © 2016 The Authors. Most of time series model are usually investigated and implemented by ARIMA and Neural Networks (NNs) model. However, ARIMA model may not be adequate for complex patterned problem while NNs model can well reveal the correlation of nonlinear pattern. Since, over-fitting due to a learning process is the main advantage of NNs as well as local trapped of parameters due to the large structure of the networks. To improve the forecast performance of both ARIMA and NNs for high accuracy, hybrid ARIMA and NNs model is alternate selected and employed to examine the Chiangmai city moat's PM-10 time series data. The experimental results demonstrated that the hybrid model outperformed best over NNs and ARIMA respectively. 2018-09-05T02:57:46Z 2018-09-05T02:57:46Z 2016-01-01 Conference Proceeding 18770509 2-s2.0-84999633655 10.1016/j.procs.2016.05.057 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84999633655&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55547
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Computer Science
spellingShingle	Computer Science Rati Wongsathan Isaravuth Seedadan A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area
description	© 2016 The Authors. Most of time series model are usually investigated and implemented by ARIMA and Neural Networks (NNs) model. However, ARIMA model may not be adequate for complex patterned problem while NNs model can well reveal the correlation of nonlinear pattern. Since, over-fitting due to a learning process is the main advantage of NNs as well as local trapped of parameters due to the large structure of the networks. To improve the forecast performance of both ARIMA and NNs for high accuracy, hybrid ARIMA and NNs model is alternate selected and employed to examine the Chiangmai city moat's PM-10 time series data. The experimental results demonstrated that the hybrid model outperformed best over NNs and ARIMA respectively.
format	Conference Proceeding
author	Rati Wongsathan Isaravuth Seedadan
author_facet	Rati Wongsathan Isaravuth Seedadan
author_sort	Rati Wongsathan
title	A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area
title_short	A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area
title_full	A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area
title_fullStr	A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area
title_full_unstemmed	A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area
title_sort	hybrid arima and neural networks model for pm-10 pollution estimation: the case of chiang mai city moat area
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84999633655&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55547
_version_	1681424526196342784

A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area

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