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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主要作者: Muhammad, Mohd. Khairul Idlan
格式: Thesis
语言:English
出版: 2012
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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
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