Time series modeling using markov and arima models

Streamflow forecasting plays important roles for flood mitigation and water resources allocation and management. Inaccurate forecasting will cause losses to water resources managers and users. The suitability of forecasting method depends on type and number of available data. Thus, the objective of...

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Main Author:	Muhammad, Mohd. Khairul Idlan
Format:	Thesis
Language:	English
Published:	2012
Subjects:	TA Engineering (General) Civil engineering (General)
Online Access:	http://eprints.utm.my/id/eprint/29783/5/MohdKhairulIdlanMFKA2012.pdf
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id	my-utm-ep.29783
record_format	uketd_dc
spelling	my-utm-ep.297832018-05-27T06:54:52Z Time series modeling using markov and arima models 2012-01 Muhammad, Mohd. Khairul Idlan TA Engineering (General). Civil engineering (General) Streamflow forecasting plays important roles for flood mitigation and water resources allocation and management. Inaccurate forecasting will cause losses to water resources managers and users. The suitability of forecasting method depends on type and number of available data. Thus, the objective of this study are to propose the streamflow forecasting methods using Markov and ARIMA models and to inspect the accuracy of Markov and ARIMA models in forecasting ability. Streamflow data of Sungai Bernam, Selangor was used. Minitab and Microsoft Excel were used to model ARIMA and Markov respectively. Criteria performance evaluation procedure that being used in this study were Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE) and Chi-square test of Normality to inspect the forecasting accuracy of the different models. The tentative model that best fits the criteria and meets the requirement for ARIMA model is ARIMA (1,1,1)(0,1,1)12. From the criteria performance evaluation procedure, ARIMA model has better performance of model for forecasting than Markov model in this study. Therefore, ARIMA model has the ability to accurately predict the future monthly streamflow for Sungai Bernam. Elsevier 2012-01 Thesis http://eprints.utm.my/id/eprint/29783/ http://eprints.utm.my/id/eprint/29783/5/MohdKhairulIdlanMFKA2012.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TA Engineering (General) Civil engineering (General)
spellingShingle	TA Engineering (General) Civil engineering (General) Muhammad, Mohd. Khairul Idlan Time series modeling using markov and arima models
description	Streamflow forecasting plays important roles for flood mitigation and water resources allocation and management. Inaccurate forecasting will cause losses to water resources managers and users. The suitability of forecasting method depends on type and number of available data. Thus, the objective of this study are to propose the streamflow forecasting methods using Markov and ARIMA models and to inspect the accuracy of Markov and ARIMA models in forecasting ability. Streamflow data of Sungai Bernam, Selangor was used. Minitab and Microsoft Excel were used to model ARIMA and Markov respectively. Criteria performance evaluation procedure that being used in this study were Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE) and Chi-square test of Normality to inspect the forecasting accuracy of the different models. The tentative model that best fits the criteria and meets the requirement for ARIMA model is ARIMA (1,1,1)(0,1,1)12. From the criteria performance evaluation procedure, ARIMA model has better performance of model for forecasting than Markov model in this study. Therefore, ARIMA model has the ability to accurately predict the future monthly streamflow for Sungai Bernam.
format	Thesis
qualification_level	Master's degree
author	Muhammad, Mohd. Khairul Idlan
author_facet	Muhammad, Mohd. Khairul Idlan
author_sort	Muhammad, Mohd. Khairul Idlan
title	Time series modeling using markov and arima models
title_short	Time series modeling using markov and arima models
title_full	Time series modeling using markov and arima models
title_fullStr	Time series modeling using markov and arima models
title_full_unstemmed	Time series modeling using markov and arima models
title_sort	time series modeling using markov and arima models
granting_institution	Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department	Faculty of Civil Engineering
publishDate	2012
url	http://eprints.utm.my/id/eprint/29783/5/MohdKhairulIdlanMFKA2012.pdf
_version_	1747815704113971200

Time series modeling using markov and arima models

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