Optimal estimating the project completion time and diagnosing the fault in the project

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%

Optimal estimating the project completion time and diagnosing the fault in the project

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%

Optimal estimating the project completion time and diagnosing the fault in the project

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%.El objetivo principal del equipo de gestión del proyecto es poner en práctica el proyecto con respecto al presupuesto, horario y cubrir las limitaciones del proyecto. Además, la realización del proyecto (especialmente los grandes proyectos,) requiere la predicción adecuada del proyecto. Gestión del valor ganado es una técnica valiosa para el análisis y control de la ejecución del proyecto y predice el costo total del proyecto antes de la finalización del proyecto. Por lo tanto, Fuzzy sistemas tales como la Red de adaptación basada en Fuzzy sistema de inferencia (ANFIS) y Estructura paralela basada en el Fuzzy Sistema (PSFS) se utilizan para predecir el tiempo de finalización del proyecto. En éste artículo, el diagrama de valor del plan se utiliza para predecir el diagrama valor en tres métodos. Estos tres métodos se basan en los PSFS y Redes Neuronales que son capaces de ser poner en práctica los proyectos en las organizaciones. Los resultados de estos tres métodos disminuyeron el error de predicción del valor obtenido diagrama de hasta 2%