ARTIFICIAL INTELLIGENCE MODEL TO ANALYZE SUSTAINABILITY MANAGEMENT OF MARITIME PORTS

Abstract

The present study exposes a methodology inspired by artificial intelligence models, consisting of the inference for the analysis of the management of the sustainability of the Spanish port system using Bayesian models. A decision-making tool has been obtained. This study works at the same time the four dimensions of sustainability, similar to Puertos del Estado. So, the study was based on the variables of port sustainability from the annual sustainability reports of Puertos del Estado. From them a probabilistic model was constructed in a directed acyclic graph that represents these variables and their conditional dependencies through a Bayesian network.. As uncertainty and imprecision are associated with the reasoning processes, Bayesian methods, such as the inference used in the research, are among the methods of approximate reasoning. Thus, the study was based on the variables of port sustainability from the annual sustainability reports of Puertos del Estado. From them a probabilistic model was constructed in a directed acyclic graph that represents these variables and their conditional dependencies through a Bayesian network The obtained results showed that, from the network structure obtained, this network can be used for the prediction of the class value of any variable to be classified. Key Words: artificial intelligence, Bayesian networks, inference, port management, sustainability. Key words: artificial intelligence, Bayesian networks, inference, port management, sustainability