Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
Ports are drivers, but at the same time they are immersed in the processes of globalization of societies. That is why they are not alien to the potential of data mining methodologies, which try to discover patterns in large volumes of data sets such as those handled in the port area: Data mining is...
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| Autores principales: | , , , |
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| Formato: | Artículo publishedVersion |
| Lenguaje: | Español |
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Facultad de Filosofía y Letras, Universidad de Buenos Aires
2018
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| Acceso en línea: | https://revistascientificas.filo.uba.ar/index.php/rtt/article/view/4937 https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=transter&d=4937_oai |
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| Sumario: | Ports are drivers, but at the same time they are immersed in the processes of globalization of societies. That is why they are not alien to the potential of data mining methodologies, which try to discover patterns in large volumes of data sets such as those handled in the port area: Data mining is a discipline linked to the artificial intelligence that, applied in a port environment, makes it possible to find new tools to increase port sustainability. This article aims to analyze port sustainability through the relationships established between sustainability variables, using artificial intelligence techniques such as Bayesian networks. The main conclusion drawn from the analysis is that the fundamental pillar of port sustainability is the institutional dimension. |
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