A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation
This paper presents a new forecasting model to improve Earned Value (EV) method of projects. This method improves earned value management system (EVMS) and forecasting time and cost for projects. These method use established consists of four variables: Scheduled Performance Index (SPI), Cost Perform...
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my.um.eprints.22842011-11-23T01:06:15Z http://eprints.um.edu.my/2284/ A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation Attarzadeh, I. Hock, O.S. QA75 Electronic computers. Computer science This paper presents a new forecasting model to improve Earned Value (EV) method of projects. This method improves earned value management system (EVMS) and forecasting time and cost for projects. These method use established consists of four variables: Scheduled Performance Index (SPI), Cost Performance Index (CPI), Cost Variance (CV), Schedule Variance (SV). The model has been validated by a simulation study using a progress generator a new software. This software was developed in Visual Studio 2008 - Visual Basic NET 2008 and Microsoft Office Project 2007 and it included some basic assumptions and data were generated day by day randomly. The results show a strong relationship between response variable and above four predictors. Therefore, it can be concluded that the model could be used in a wide range of projects for EAC estimation. 2009 Conference or Workshop Item PeerReviewed Attarzadeh, I. and Hock, O.S. (2009) A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation. In: International Conference on Information Management and Engineering, APR 03-05, 2009 , Kuala Lumpur, MALAYSIA. http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=Refine&qid=3&SID=S1olJgKm7P7b1AoN2hb&page=17&doc=161&cacheurlFromRightClick=no |
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QA75 Electronic computers. Computer science Attarzadeh, I. Hock, O.S. A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
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This paper presents a new forecasting model to improve Earned Value (EV) method of projects. This method improves earned value management system (EVMS) and forecasting time and cost for projects. These method use established consists of four variables: Scheduled Performance Index (SPI), Cost Performance Index (CPI), Cost Variance (CV), Schedule Variance (SV). The model has been validated by a simulation study using a progress generator a new software. This software was developed in Visual Studio 2008 - Visual Basic NET 2008 and Microsoft Office Project 2007 and it included some basic assumptions and data were generated day by day randomly. The results show a strong relationship between response variable and above four predictors. Therefore, it can be concluded that the model could be used in a wide range of projects for EAC estimation. |
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Conference or Workshop Item |
author |
Attarzadeh, I. Hock, O.S. |
author_facet |
Attarzadeh, I. Hock, O.S. |
author_sort |
Attarzadeh, I. |
title |
A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
title_short |
A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
title_full |
A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
title_fullStr |
A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
title_full_unstemmed |
A new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
title_sort |
new forecasting model to improve earned value index to achieve an accurate project time and cost estimation |
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2009 |
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http://eprints.um.edu.my/2284/ http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=Refine&qid=3&SID=S1olJgKm7P7b1AoN2hb&page=17&doc=161&cacheurlFromRightClick=no |
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13.214268 |