A model of integration among prediction tools: applied study to road freight transportation

Blois, Henrique Dias; Martins, Ricardo Silveira

doi:10.1016/j.rausp.2016.09.005

Cited by 2 publications

(3 citation statements)

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“…Blois and Martins [21] built a predictive model for scenarios intended to identify key investment areas in the road freight network. The primary goal adopted in the scenario analysis was to reduce pollution.…”

Section: Transport Development Scenariosmentioning

confidence: 99%

“…The authors of this publication, conducting research in this field, found it justified to take actions towards defining scenarios for development of multimodal transport within the cross-border area of Poland-Czech Republic-Slovakia. The literature on freight transport development scenarios mainly refers to either the development of single modes of transport (mostly road transport) [19,20], or analyses conducted in relation to national transport systems [21,22]. In this paper, an attempt is made to develop scenarios aimed at the development of multimodal transport and its implementation within the cross-border area in the 2030 perspective.…”

Section: Introductionmentioning

confidence: 99%

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Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

et al. 2020

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As the demand for transport is growing, more and more attention is being paid to its quality aspects. These include, among other things, efficiency, safety, and a continuous effort to reduce external costs. That is why the transport policies of the EU countries and individual regions are increasingly addressing the issue of sustainable transport development. Multimodal transport, which is seen as a key element to effectively counterbalance the dominant role of vehicle transport in the economic progress of the European Community, plays an important role in these programmes. For consistency and continuity of freight flows, cooperation between neighbouring countries and regions is essential. The future of multimodal freight transport within the cross-border area of Poland, Czech Republic and Slovakia is not as evident as the transport policies imply. Therefore, the purpose of the paper is to identify a set of factors determining the development of multimodal transport within the cross-border area of TRITIA (The European Grouping of Territorial Cooperation of the four regional governments of Moravian-Silesian Region (CZ), Opole Voivodeship (PL), Silesian Voivodeship (PL) and Žilina Self-governing Region (SK)) and to develop four scenarios, the execution of which in the 2030 perspective depends on the implementation of cross-border infrastructure and organisational projects and the increasing level of cooperation in the field of multimodal transport. The article contains the methodology for developing scenarios of multimodal freight transport development. The research showed that initiating activities targeted at the development of multimodal transport within the cross-border area requires the involvement of all participants in the process, i.e., all countries (Poland, Czech Republic and Slovakia), along with many different stakeholders. The future development of multimodal transport as provided for in the scenarios is not linearly correlated with the increase in cooperation and the number of implemented infrastructure and organisational projects. It is vital for future research to define the role of stakeholders both in terms of cooperation and collaboration development.

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Section: Transport Development Scenariosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

et al. 2020

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“…Quanto aos modelos preditivos para o frete rodoviário, trabalhos anteriores fazem-no mais comumente através do uso de técnicas estatísticas como regressão e séries temporais (OLIVEIRA; YAMAKAMI, 2006, CANGUSSU et al, 2013, COSTA, 2014FERREIRA, 2016;BLOIS;MARTINS, 2017;COPPE et al, 2020).…”

Section: Introductionunclassified

Predição de fretes agrícolas baseado na aplicação de técnicas de aprendizado de máquina

Eduardo Souza Moreira

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The grain freight cost is one of the biggest obstacles for the Brazil's competitiveness in international scenario. The road freight still is majority adopted on agricultural products transporting, and not unusual, that is the only choice to carry them. The cost weight, felt by the agribusiness operators, which work with supply chains might be decreased after the adoption of a freight management system. A promising alternative to deal with this challenge is the use of data mining techniques, which are able to extract patterns and trends in large amounts of data, which is why they have been increasingly used to support management decision in different areas, in place of intuition and resolutions based on experience. Thus, the project major goal is to develop and implement an intelligent system for forecasting road freight prices for agricultural grains. Thus, the aim of this research is predicting the freight price of agricultural commodities using models generated from Multi Layer Perceptron (MLP) and Support Vector Regression (SVR). The massive use of freight road in the logistic and grain distribution, reinforces the importance of predicting freight prices, therefore a system that could provide that kind of information to agribusiness managers and decision makers, would be critical on their daily activities. he results indicated that both techniques were efficient in estimating agricultural grain road freight prices in terms of R-squared and root mean square error (RMSE). Comparing the techniques, the SVR technique outperformed achieving an R-squared of 0.8921 and RMSE of 8.0464 for the range of routes up to 600km and 0.8924 and 21.1167 for routes longer than 600km, adopting specialized models for each data partition. In the other hand MLP resulted an R-squared 0.8785 and 8.5404 RMSE for short routes and 0.8506 and 24.8818 for long routes also making use of specialized models. In terms of using the general model or with partitioning the dataset as a function of distance traveled on the transportation route, using two individual models specialized in partitioning the set of routes into two ranges of up to 600km or greater, performed better when compared to adopting a general model for all two ranges of distances. This confirms the hypothesis that road freight prices show different behavior for different distance ranges.

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A model of integration among prediction tools: applied study to road freight transportation

Cited by 2 publications

References 8 publications

Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

Predição de fretes agrícolas baseado na aplicação de técnicas de aprendizado de máquina

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