| Autor: |
García, José Alejandro Lugo, Peña, Anié Bermudez, Pérez, Pedro Yobanis Piñero, Pérez, Rafael Bello |
| Zdroj: |
International Journal of Computational Intelligence Systems; January 2017, Vol. 10 Issue: 1 p320-335, 16p |
| Abstrakt: |
Project monitoring and control by using key performance indicators has become a widespread method for decision-making in project-oriented organizations. However, the current schools and IT tools created for this purpose require an upgrade in design due to imprecision, vagueness or uncertainty present in the raw data and changing conditions in management styles. Moreover, the use of proprietary technologies in developing nations represents high costs for governments and obstacles to achieving its technological sovereignty. This paper studies the trends and challenges in project control through computational intelligence methods. It also examines schools and technological tools to manage projects, as well as open source software for the application of computational intelligence techniques over the past decades. Current tendencies and improvement areas, valuing niche markets with high applicability around the thematic goal it is also analyzed. The contribution of this study is related to the predicted necessity of constructing new models and IT tools for project control which integrate machine learning-based approaches and treatment of imprecision, vagueness or uncertainty in the information, using key performance indicators linked to fundamental knowledge areas. The implementation of new libraries for learning evaluation in project control with open source software tools, opens a field of research related to increase technological integration with IT project management tools. The content under discussion provides support to improve decision-making in project-oriented organizations. |
| Databáze: |
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