Seaport Sustainable: Use of Artificial Intelligence to Evaluate Liquid Natural Gas Utilization in Short Sea Shipping

Abstract

In the present research, a methodology is developed to determine the relationship between the variables that define the use of liquefied natural gas in short sea shipping in Europe, through the use of data-mining techniques. The project takes place in the European space, which includes data from 30 countries, the 28 members of the European Union plus Norway and Iceland. A Bayesian network is constructed with the 35 indicators selected, which are classified into five different categories: international trade and transport, economy and finance, population and social condition, environment and energy, and institutional and political. It is found that capacity of liquefied natural gas regasification terminals under construction and modal distribution of cargo transport by inland waters are the two root nodes of the network. In addition, the variables of transport and international trade and economy and finance become the most important in the decision to implement liquefied natural gas as marine fuel, while those of environment and energy and population and condition are the most dependent on the network.

Actualización del marco estratégico para el sistema portuario español empleando un análisis DAFO

“…The digital transformation that results goes far beyond mere technological considerations. In fact, we are going to talk very little about technology, and more about diagnosis (the https://doi.org/10.25100/cdea.v36i68.9459 patient) and planning (González-Cancelas, Molina Serrano, and Soler-Flores, 2019).…”

Instruments Used in Short Sea Shipping Research between 2002 and 2019

“…Subsequently, the next popular SSS research area is on the attractiveness and competitiveness of SSS in a multimodal transport chain ( [39], [131], [68], [35], [71], [114], [77], [66], [120], [34], [27], [37], [42], [87], [78], [20], [62], [95], [19], [103], [8], [21], and [9]). This is followed by research on policy, subsidization, funding and government assistance in SSS and multimodal transportation network as the third most popular area ( [132], [44], [59], [60], [82], [114], [112], [12], [51], [81], and [92]).…”

“…From the European perspectives [39] employed the Data-Mining Techniques to evaluate liquid natural gas (LNG) utilization in SSS. This study found that the capacity of LNG regasification depots under structure and modal distribution of freight transport by inland waters are the dual core nodes of the linkage.…”

Predictive Model for LNG Ship Routing applying Machine Learning

“…Liquefied Natural Gas (LNG) is natural gas that has been cooled down below -163°C to become liquid [15]. Shipping costs considerably influences the LNG competitiveness [16]. Among them are listed some specific costs such as ship's fuel cost and others more general such as loading and unloading port fares [17].…”