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Pattern Analysis and Applications

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12-02-2020 | Original Article

Analysing the intermeshed patterns of road transportation and macroeconomic indicators through neural and clustering techniques

Authors: Carlos Alonso de Armiño, Miguel Ángel Manzanedo, Álvaro Herrero

Published in: Pattern Analysis and Applications | Issue 3/2020

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Abstract

As is widely acknowledged, the transportation of goods by road can, in one way or another, be linked to a range of macroeconomic indicators. A hybrid artificial intelligence system is proposed in this paper to analyse the interaction between transportation patterns and the economy. The temporal patterns of road transportation and macroeconomic trends are studied, by combining the use of both (supervised and unsupervised) neural networks and clustering techniques. The proposed system is validated, by establishing links between road transportation data from Spain and macroeconomic trends over 6 years (2011–2017). The results reveal an interesting inner structure of the data, through data visualizations of intermeshed relations between road transportation patterns and macroeconomic indicators. The same data structure was also visible in the output of the clustering techniques. Furthermore, a number of high-quality predictions were advanced by processing the road transportation data as time series, and forecasting the future values of the main series. These results demonstrated the validity of the proposed linkage between road transportation data and macroeconomic indicators.

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Title: Analysing the intermeshed patterns of road transportation and macroeconomic indicators through neural and clustering techniques
Authors: Carlos Alonso de Armiño
Miguel Ángel Manzanedo
Álvaro Herrero
Publication date: 12-02-2020
Publisher: Springer London
Published in: Pattern Analysis and Applications / Issue 3/2020
Print ISSN: 1433-7541
Electronic ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-020-00872-x

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