CUBE ONLINE ANALYTICAL MODEL (COLAM) IN THE RIVER SHIPPING LOGISTIC FORECASTING

Authors

  • Natalia Verbitskaya Ural State Forestry Engineering University, Faculty of Forestry, Yekaterinburg
  • Darko B. Vuković Ural Federal University, Graduate School of Economics and Management, Yekaterinburg Geographical Institute "Jovan Cvijić" SASA, Belgrade
  • Andrey Mehrentsev Ural State Forestry Engineering University, Faculty of Forestry, Yekaterinburg
  • Dejana Jakovljević Geographical Institute "Jovan Cvijić" SASA, Belgrade Moscow State Pedagogical University, Russian Institute for Advanced Studies, Moscow
  • Aleksandra Vujko Novi Sad Business School, Novi Sad South Ural State University, Institute of Sports, Tourism and Service, Chelyabinsk

DOI:

https://doi.org/10.2298/IJGI1802297V

Keywords:

economic geography, COLAM, river shipping, hazards, transport logistics

Abstract

In this paper authors developed Cube Online Analytical Model (COLAM) which should anticipate various restrictions and hazards in river transport system. The aim is to construct a theoretical model which will predict certain delays in transport time caused by topographic and hydrographic constraints, natural hazards (such as ice, floods and droughts), economic and political constraints (tariff barriers between the countries, operating costs, terminal costs and sanctions, the threat of war, etc.) and different technical accidents. COLAM integrates hydroinformatic and hydrologic base of knowledge with real time and gives possibility to provide information for economic queries with different hierarchy of time. COLAM is methodological and practical instrument for this challenge. It integrates hydroinformatic and hydrologic base of knowledge with real time. The model in each concrete case is created to receive information about possible changing of navigation periods on the base of multi-dimension all of three groups of risks (natural hazards, social and technical hazards) as also their combinations.

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References

Fernández, N., Jaimes, W., & Altamiranda, E. (2010). Neurro-fuzzy modeling for level prediction for the navigation sector on the Magdalena River (Colombia). Journal of Hydroinformatics, 12(1), 36–50. doi: http://dx.doi.org/10.2166/hydro.2010.059

Gelfan, A. N, & Moreido, V. M. (2014). Dynamic-stochastic modeling of snow cover formation on the European territory of Russia. Lëd i Sneg, 54(2), 44–52. doi: https://doi.org/10.15356/2076-6734-2014-2-44-52

Gregory, K. J., Benito, G., Dikau, R., Golosov, V., Johnstone, E. C., Jones, J. A., Macklin, M. G., Parsons, A. J., Passmore, D. G., Poesen, J., Soja, R., Starkel, L., Thorndycraft, V. R., & Walling, D. E. (2006). Past hydrological events and global change. Hydrological Processes, 20(1), 199–204. doi: https://doi.org/10.1002/hyp.6105

Mynett, A. E., & Vojinovic, Z. (2009). Hydroinformatics in multi-colors – part red: urban flood and disaster management. Journal of Hydroinformatics, 11(3–4), 166–180. doi: http://dx.doi.org/10.2166/hydro.2009.027

Petrova, E. G. (2011). Natural factors of technological accidents: the case of Russia. Natural Hazards and Earth System Sciences, 11(8), 2227–2234. doi: https://doi.org/10.5194/nhess-11-2227-2011

Roushangar, K., Hassanzadeh, Y., Keyneyad, M. A., Nourani, V., & Mouaze, D. (2011). Studying of flow model and bed load transport in a coarse bed river: case study — Aland River, Iran. Journal of Hydroinformatics, 13(4), 850–866. doi: https://doi.org/10.2166/hydro.2010.010

Thomsen, E. (2002). OLAP Solutions: Building Multidimensional Information Systems (2nd Ed). Wiley: New York, USA.

Vuković, D. B., Simeunović, I. R., Zalesov, S., Yamashkin, A. A., & Shpak, N. (2015). Influence of summer temperatures on basic economic and tourism indicators of the Middle Mediterranean. Thermal Science, 19(2), S361–S370. doi: http://dx.doi.org/10.2298/TSCI150328086V

Weber, A., Zhang, J., Nardin, A., Sukhodolov, A., & Wolter, C. (2016). Modelling the Influence of Aquatic Vegetation on the Hydrodynamics of an Alternative Bank Protection Measure in a Navigable Waterway. River Research and Applications, 32(10), 2071–2080. doi: http://dx.doi.org/10.1002/rra.3052

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Published

2018-08-24

How to Cite

Verbitskaya, N., Vuković, D. B., Mehrentsev, A., Jakovljević, D., & Vujko, A. (2018). CUBE ONLINE ANALYTICAL MODEL (COLAM) IN THE RIVER SHIPPING LOGISTIC FORECASTING. Journal of the Geographical Institute “Jovan Cvijić” SASA, 68(2), 297–304. https://doi.org/10.2298/IJGI1802297V

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