RT info:eu-repo/semantics/article
T1 An Intelligent Visualisation Tool to Analyse the Sustainability of Road Transportation
A1 Alonso de Armiño Pérez, Carlos
A1 Urda Muñoz, Daniel
A1 Alcalde Delgado, Roberto
A1 García Pineda, Santiago
A1 Herrero Cosío, Álvaro
K1 Artificial intelligence
K1 Unsupervised machine learning
K1 Exploratory projection pursuit
K1 Clustering
K1 Road transportation
K1 Transport sustainability
K1 Age of transport means
K1 Transportes
K1 Transportation
K1 Informática
K1 Computer science
AB Road transport is an integral part of economic activity and is therefore essential for its development. On the downside, it accounts for 30% of the world’s GHG emissions, almost a third of which correspond to the transport of freight in heavy goods vehicles by road. Additionally, means of transport are still evolving technically and are subject to ever more demanding regulations, which aim to reduce their emissions. In order to analyse the sustainability of this activity, this study proposes the application of novel Artificial Intelligence techniques (more specifically, Machine Learning). In this research, the use of Hybrid Unsupervised Exploratory Plots is broadened with new Exploratory Projection Pursuit techniques. These, together with clustering techniques, form an intelligent visualisation tool that allows knowledge to be obtained from a previously unknown dataset. The proposal is tested with a large dataset from the official survey for road transport in Spain, which was conducted over a period of 7 years. The results obtained are interesting and provide encouraging evidence for the use of this tool as a means of intelligent analysis on the subject of developments in the sustainability of road transportation.
PB MDPI
SN 2071-1050
YR 2022
FD 2022-01
LK http://hdl.handle.net/10259/6634
UL http://hdl.handle.net/10259/6634
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 24-dic-2024