Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence

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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: Molina Serrano, Beatriz, González-Cancelas, Nicoletta, Soler-Flores, Francisco, Camarero Orive, Alberto
Formato: Artículo publishedVersion
Lenguaje:Español
Publicado: Facultad de Filosofía y Letras, Universidad de Buenos Aires 2018
Materias:
sostenibilidad
puertos
inteligencia artificial
redes bayesianas
sustainability
ports
artificial intelligence
bayesian networks
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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Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires
id I28-R145-4937_oai
record_format dspace
spelling I28-R145-4937_oai2025-11-17 Molina Serrano, Beatriz González-Cancelas, Nicoletta Soler-Flores, Francisco Camarero Orive, Alberto 2018-05-29 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.  Los puertos son impulsores, pero a la vez están inmersos en los procesos de globalización de las sociedades. Es por ello que no son ajenos a la potencialidad de las metodologías de minería de datos, las cuales intentan descubrir patrones en grandes volúmenes de conjuntos de datos como los que se manejan en el ámbito portuario: La minería de datos es una disciplina ligada a la inteligencia artificial que, aplicado en un entorno portuario, posibilita encontrar nuevas herramientas para aumentar la sostenibilidad portuaria. Este artículo pretende analizar la sostenibilidad portuaria a través de las relaciones que se establecen entre variables de sostenibilidad, empleando para ello técnicas de inteligencia artificial como son las redes bayesianas. La principal conclusión que se extrae del análisis es que el pilar fundamental de la sostenibilidad portuaria es la dimensión institucional.  application/pdf https://revistascientificas.filo.uba.ar/index.php/rtt/article/view/4937 10.34096/rtt.i18.4937 spa Facultad de Filosofía y Letras, Universidad de Buenos Aires https://revistascientificas.filo.uba.ar/index.php/rtt/article/view/4937/4431 Revista Transporte y Territorio; No. 18 (2018): (enero-junio) - Caminos; 264-284 Revista Transporte y Territorio; Núm. 18 (2018): (enero-junio) - Caminos; 264-284 1852-7175 sostenibilidad puertos inteligencia artificial redes bayesianas sustainability ports artificial intelligence bayesian networks Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence Análisis de las dimensiones institucional, económica, social y ambiental portuarias a través de inteligencia artificial info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=transter&d=4937_oai
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-145
collection Repositorio Digital de la Universidad de Buenos Aires (UBA)
language Español
orig_language_str_mv spa
topic sostenibilidad
puertos
inteligencia artificial
redes bayesianas
sustainability
ports
artificial intelligence
bayesian networks
spellingShingle sostenibilidad
puertos
inteligencia artificial
redes bayesianas
sustainability
ports
artificial intelligence
bayesian networks
Molina Serrano, Beatriz
González-Cancelas, Nicoletta
Soler-Flores, Francisco
Camarero Orive, Alberto
Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
topic_facet sostenibilidad
puertos
inteligencia artificial
redes bayesianas
sustainability
ports
artificial intelligence
bayesian networks
description 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. 
format Artículo
publishedVersion
author Molina Serrano, Beatriz
González-Cancelas, Nicoletta
Soler-Flores, Francisco
Camarero Orive, Alberto
author_facet Molina Serrano, Beatriz
González-Cancelas, Nicoletta
Soler-Flores, Francisco
Camarero Orive, Alberto
author_sort Molina Serrano, Beatriz
title Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
title_short Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
title_full Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
title_fullStr Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
title_full_unstemmed Analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
title_sort analysis of port institutional, economic, social and environmental dimensions using artificial intelligence
publisher Facultad de Filosofía y Letras, Universidad de Buenos Aires
publishDate 2018
url 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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