A Residual Grey Prediction Model for Predicting S-curves in Projects
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- 作者：José ; Ramó ; n San Cristó ; bal ; jose.sancristobal@unican.es" class="auth_mail" title="E-mail the corresponding author ; Francisco Correa ; Marí ; a Antonia Gonzá ; lez ; Emma Diaz Ruiz de Navamuel ; Ernesto Madariaga ; André ; s Ortega ; Sergio Ló ; pez ; Manuel Trueba
- 关键词：S-curves ; Forecasting ; Grey model.
- 刊名：Procedia Computer Science
- 出版年：2015
- 出版时间：2015
- 年：2015
- 卷：64
- 期：Complete
- 页码：586-593
- 全文大小：361 K
文摘
S-curves are usually taken as expression of project progress and have become a requisite tool for project managers through the execution phase. The common methodology for predicting S-curve forecasting models is based on classifying projects into groups and producing a standard S-curve for each group using multiple linear regression techniques. Traditional regression models taken to fit individual projects require a large amount of data and make many strict assumptions regarding statistical distribution of the data. The grey system theory, however, is well suited to study the behavior of a system with incomplete information or limited amount of discrete data. Easy of use and accuracy, two significant criteria for project managers when choosing a forecasting model, are considered two additional attributes of the grey system theory. This paper proposes a residual Grey prediction model to forecast the actual cost and the cost at completion of a project based on the grey system theory. Results show that the accuracy of the forecasting model is highly efficient.