Development of data modification method for optimization of forecasting performance

Dynamic nature of influencing parameters on market variations prevents decision makers to have a broad vision about possible future changes as an important factor in an organization survival. A precise forecast of both price and demand is a vital issue to illustrate market changes, and prosperity of...

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Main Author:	Seyedi, Seyednavid
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QA76 Computer software
Online Access:	http://eprints.utm.my/id/eprint/42096/1/SeyednavidSeyediMFKM2013.pdf
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id	my-utm-ep.42096
record_format	uketd_dc
spelling	my-utm-ep.420962017-07-06T04:47:03Z Development of data modification method for optimization of forecasting performance 2013 Seyedi, Seyednavid QA76 Computer software Dynamic nature of influencing parameters on market variations prevents decision makers to have a broad vision about possible future changes as an important factor in an organization survival. A precise forecast of both price and demand is a vital issue to illustrate market changes, and prosperity of plans and investments. The main purpose of this study is to develop a quantitative method, which encompasses human user cognition in order to modify timeseries, before being used as an input for forecast models. Some studies conclude ARIMA-ANN hybrid model as the best forecasting model in comparison with its individual models. However, this claim is rejected in some cases. It is a reason to check the performance of individual models in addition to hybrid model in new cases. Historical data are collected from two case studies in manufacturing and service industries. These data are modified by the developed method. Both original and modified data are implemented as inputs for ARIMA, artificial neural network (ANN), and ARIMA-ANN forecast models. The square errors (MSE) and mean absolute percentage error (MAPE). In both case erformance. In predictions 2013 Thesis http://eprints.utm.my/id/eprint/42096/ http://eprints.utm.my/id/eprint/42096/1/SeyednavidSeyediMFKM2013.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:81492?queryType=vitalDismax&query=Development+of+data+modification+method+for+optimization+of+forecasting+performance&public=true masters Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Seyedi, Seyednavid Development of data modification method for optimization of forecasting performance
description	Dynamic nature of influencing parameters on market variations prevents decision makers to have a broad vision about possible future changes as an important factor in an organization survival. A precise forecast of both price and demand is a vital issue to illustrate market changes, and prosperity of plans and investments. The main purpose of this study is to develop a quantitative method, which encompasses human user cognition in order to modify timeseries, before being used as an input for forecast models. Some studies conclude ARIMA-ANN hybrid model as the best forecasting model in comparison with its individual models. However, this claim is rejected in some cases. It is a reason to check the performance of individual models in addition to hybrid model in new cases. Historical data are collected from two case studies in manufacturing and service industries. These data are modified by the developed method. Both original and modified data are implemented as inputs for ARIMA, artificial neural network (ANN), and ARIMA-ANN forecast models. The square errors (MSE) and mean absolute percentage error (MAPE). In both case erformance. In predictions
format	Thesis
qualification_level	Master's degree
author	Seyedi, Seyednavid
author_facet	Seyedi, Seyednavid
author_sort	Seyedi, Seyednavid
title	Development of data modification method for optimization of forecasting performance
title_short	Development of data modification method for optimization of forecasting performance
title_full	Development of data modification method for optimization of forecasting performance
title_fullStr	Development of data modification method for optimization of forecasting performance
title_full_unstemmed	Development of data modification method for optimization of forecasting performance
title_sort	development of data modification method for optimization of forecasting performance
granting_institution	Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department	Faculty of Mechanical Engineering
publishDate	2013
url	http://eprints.utm.my/id/eprint/42096/1/SeyednavidSeyediMFKM2013.pdf
_version_	1747816688770875392

Development of data modification method for optimization of forecasting performance

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