Optimal estimating the project completion time and diagnosing the fault in the project
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| Format: | Artículo científico |
| Language: | en |
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Universidad Nacional de Colombia
2016
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| _version_ | 1876461887931023360 |
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| author | M. T. Hajali-Mohamad |
| author_facet | M. T. Hajali-Mohamad |
| contents | Optimal estimating the project completion time and diagnosing the fault in the project M. T. Hajali-Mohamad M. R. Mosavi K. Shahanaghi Ingeniería PSFS ANFIS Plan Value Earned Value Neural Network The main objective of the project management team is to implement the project taking into consideration the Budget, schedule and constraints. In addition, project accomplishment, especially with large projects, requires the project to be correctly envisaged. Earned value (EV) management is a valuable technique for analyzing and controlling the performance of the project and predicting the total cost before its completion. Thus, fuzzy systems such as Adaptive Network based on the Fuzzy Inference System (ANFIS) and Parallel Structure based on the Fuzzy System (PSFS) are used to predict the project completion time. In this paper, the plan value diagram is used to predict the earn value diagram using three methods. These three methods are based on the PSFS and Neural Networks (NNs), which help with the implementation of the projects in organizations. The results of these three methods decreased the prediction error of the EV diagram by up to 2%. 2016 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49644128016 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.195 Vol.83 |
| format | Artículo científico |
| id | redalyc_49644128016 |
| institution | Redalyc |
| language | en |
| publishDate | 2016 |
| publisher | Universidad Nacional de Colombia |
| spellingShingle | Optimal estimating the project completion time and diagnosing the fault in the project M. T. Hajali-Mohamad Ingeniería PSFS ANFIS Plan Value Earned Value Neural Network Optimal estimating the project completion time and diagnosing the fault in the project M. T. Hajali-Mohamad M. R. Mosavi K. Shahanaghi Ingeniería PSFS ANFIS Plan Value Earned Value Neural Network The main objective of the project management team is to implement the project taking into consideration the Budget, schedule and constraints. In addition, project accomplishment, especially with large projects, requires the project to be correctly envisaged. Earned value (EV) management is a valuable technique for analyzing and controlling the performance of the project and predicting the total cost before its completion. Thus, fuzzy systems such as Adaptive Network based on the Fuzzy Inference System (ANFIS) and Parallel Structure based on the Fuzzy System (PSFS) are used to predict the project completion time. In this paper, the plan value diagram is used to predict the earn value diagram using three methods. These three methods are based on the PSFS and Neural Networks (NNs), which help with the implementation of the projects in organizations. The results of these three methods decreased the prediction error of the EV diagram by up to 2%. 2016 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49644128016 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.195 Vol.83 |
| title | Optimal estimating the project completion time and diagnosing the fault in the project |
| topic | Ingeniería PSFS ANFIS Plan Value Earned Value Neural Network |
| url | https://www.redalyc.org/articulo.oa?id=49644128016 |