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A residual Grey prediction model for predicting S-curves in projects

Abstract: 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.

 Autoría: Cristóbal J., Correa F., González M., De Navamuel E., Madariaga E., Ortega A., López S., Trueba M.,

 Congreso: International Conference on Project MANagement: ProjMAN ( 2015, Vilamoura, Portugal)

 Editorial: Elsevier

 Año de publicación: 2015

 Nº de páginas: 8

 Tipo de publicación: Comunicación a Congreso

 DOI: 10.1016/j.procs.2015.08.570

 ISSN: 1877-0509

 Url de la publicación: http://dx.doi.org/10.1016/j.procs.2015.08.570