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Comparative Modelling of Interregional Transport Flows Applications to Multimodal European Freight Transport
TLDR
In this article, the authors compare the predictive power of logit and neural network models for multimodal network flows and show that the predictive potential of neural networks is higher than logit analysis, and the results are also used to investigate the implications of various road tax systems on various segments of the European road network.Abstract:
This paper aims to compare the descriptive and predictive power of two classes of statistical estimation models for multimodal network flows, viz. the logit model and the neural network model. The application concerns a large data set on inter-regional European freight flows for two commodity categories (food and chemicals). After an exposition of policy issues, methodological and modelling questions and the database, a variety of experiments is carried out. The results show that in general the predictive potential of neural network models is higher than that of logit analysis. The statistical results are also used to investigate the implications of various road tax systems (e.g., e&axes) on various segments of the European road networkread more
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Evaluation of consolidation center cargo capacity and loctions for China railway express
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Towards an inclusive circular economy: Quantifying the spatial flows of e-waste through the informal sector in China
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Opening the Interregional Trade ‘‘Black Box’’: The C-Intereg Database for the Spanish Economy (1995—2005)
TL;DR: This paper showed that national trade tends to be more intense than international trade and that intra-and inter-regional trade tend to be less intense than inter-region trade, owing to the dearth of border effects.
Tourism’s impact on climate change and its mitigation challenges: How can tourism become ‘climatically sustainable’?
TL;DR: In this article, the authors examined what the main drivers for tourism's CO2 emissions development are and indicated what the tourism sector should look like in terms of improved energy efficiencies and volumes of trips, guest-nights, transport distances and transport mode choice to fit a "climatically sustainable development".
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The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system
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References
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Warren S. McCulloch,Walter Pitts +1 more
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Discrete Choice Analysis: Theory and Application to Travel Demand
Moshe Ben-Akiva,Steven R. Lerman +1 more
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