DATA MINING WORKSPACE AS AN OPTIMIZATION PREDICTION TECHNIQUE FOR SOLVING TRANSPORT PROBLEMS

Publications

Share / Export Citation / Email / Print / Text size:

Transport Problems

Silesian University of Technology

Subject: Economics, Transportation, Transportation Science & Technology

GET ALERTS

eISSN: 2300-861X

DESCRIPTION

10
Reader(s)
31
Visit(s)
0
Comment(s)
0
Share(s)

SEARCH WITHIN CONTENT

FIND ARTICLE

Volume / Issue / page

Related articles

VOLUME 11 , ISSUE 3 (September 2016) > List of articles

DATA MINING WORKSPACE AS AN OPTIMIZATION PREDICTION TECHNIQUE FOR SOLVING TRANSPORT PROBLEMS

Anastasiia KUPTCOVA / Petr PRŮŠA * / Gabriel FEDORKO / Vieroslav MOLNÁR

Keywords : time-series prediction, data mining, neural network, modelling

Citation Information : Transport Problems. Volume 11, Issue 3, Pages 21-31, DOI: https://doi.org/10.20858/tp.2016.11.3.3

License : (CC BY-SA 4.0)

Received Date : 22-April-2015 / Accepted: 22-August-2016 / Published Online: 24-February-2017

ARTICLE

ABSTRACT

Summary. This article addresses the study related to forecasting with an actual high-speed decision making under careful modelling of time series data. The study uses data-mining modelling for algorithmic optimization of transport goals. Our finding brings to the future adequate techniques for the fitting of a prediction model. This model is going to be used for analyses of the future transaction costs in the frontiers of the Czech Republic. Time series prediction methods for the performance of prediction models in the package of Statistics are Exponential, ARIMA and Neural Network approaches. The primary target for a predictive scenario in the data mining workspace is to provide modelling data faster and with more versatility than the other management techniques.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

  1. Arlt, J. & Arltová, M. Ekonomické časové řady. Praha: Professional Publishing. 2009. 290 p. [In Czech: Arlt &, J. & Arltová, M. Economic time series. Prague: Professional Publishing].
  2. Asteriou, D. & Stephen G. Hall. Applied Econometrics. New York: Palgrave Macmillan. 2011. 512 p.
  3. Palit, A.K. & Popovic, D. Computational Intelligence in Time Series Forecasting Theory and Engineering Applications. New York: Springer Science & Business Media. 2006. 393 p.
  4. Burian, P. Internet inteligentních aktivit. Praha: Grada Publishing, a.s. 2014. 336 p. [In Czech: Burian, P. Intelligent Internet activities. Prague: Grada Publishing, a.s. 2014].
  5. Brooks, Ch. Introductory Econometrics for Finance. United Kingdom: Cambridge University Press. 2008. 648 p.
  6. Cipra, T. Analýza časových řad s aplikacemi v ekonomii. Praha: SNTL. 1986. 246 p. [In Czech: Cipra, T. Time series analysis with applications in economics. Prague: SNTL].
  7. Lee, C.F. & Lee, J.C. & Lee, A.C. Statistics for Business and Financial Economics. Singapore: World Scientific. 2000. 976 p.
  8. Dostál, P. & Rais, K. & Sojka, Z. Pokročilé metody manažerského rozhodování: konkrétní příklady využití metod v praxi. Praha: Publishing a.s. 2005. 166 p. [In Czech: Dostál, P. & Rais, K. & Sojka, Z. Advanced methods of managerial decision: concrete examples of methods in practice. Prague: Publishing a.s. 2005].
  9. Fedorko, G. & Čujan, Z. Optimization in modern business practice. In: Int. Conf. Ind. Logist. ICIL 2014 - Conf. Proc. Zagreb. Faculty of Mechanical Engineering and Naval Architecture. 2014. P. 167–175.
  10. Giudici, P. Applied Data Mining: Statistical Methods for Business and Industry. New Jersey: John Wiley & Sons. 2005. 376 p.
  11. Linoff, G.S. & Berry, M.J.A. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management. New Jersey: John Wiley & Sons. 2011. 888 p.
  12. Jiřina, M. Jak na neuronové sítě v programu STATISTICA - neuronové sítě. StatSoft. Praha: Publishing a.s. 2008. 47 p. [In Check: Jiřina, M. As neural networks in the STATISTICA - neural networks. Prague: Publishing a.s. 2008.].
  13. Michaels, J.V. & Wood, W.P. Design to Cost. New Jersey: John Wiley & Sons. 1989. 413 p.
  14. Arlt, J. & Arltová, M. Příklady z analýzy ekonomických časových řad. Praha: Vysoká škola ekonomická. 1997. 147 p. [In Czech: Arlt, J. & Arltová, M. Examples of analysis of economic time series. Prague: University of Economics].
  15. Mrówczyńska, B. & Łachacz, K. & Haniszewski, T. & Sładkowski, A. A comparison of forecasting the results of road transportation needs. Transport. 2012. Vol. 27. No. 1. P. 73-78. ISSN 1648-4142.
  16. Milenković, M.S. & Bojović, N.J. &, Švadlenka, L. & Melichar, V. A stochastic model predictive control to heterogeneous rail freight car fleet sizing problem. Transportation Research Part E: Logistics and Transportation Review. 2015. 82. P. 162-198.
  17. Mun. J. Modeling Risk: Applying Monte Carlo Risk Simulation, Strategic Real Options, Stochastic Forecasting, and Portfolio Optimization. New Jersey: John Wiley & Sons. 2010. 976 p.
  18. Berry, M.J.A. & Linoff, G.S. Mastering Data mining: The art and science of customer relationship management. New Delhi: Wiley India Pvt. Limited. 2008. 512 p.
  19. Novák, M. & Beck, C.H. Umělé neuronové sítě. Praha: C. H. Beck. 1998. 382 p. [In Czech: Novák, M. & Beck, C.H. Artificial neural networks. Prague: C. H. Beck].
  20. Picton, F. Neural networks. New York: Palgrave Macmillan. 2000.195 p.
  21. Pankratz, A. Forecasting with Univariate Box - Jenkins Models: Concepts and Cases. New Jersey: John Wiley & Sons. 2009. 576 p.
  22. Pojkarová, K. Ekonometrie a prognostika v dopravě. Pardubice: Univerzita Pardubice. Dopravní fakulta Jana Pernera. 2013. 100 p. [In Check: Pojkarová, K. Econometrics and forecasting in transport. Pardubice: University of Pardubice].
  23. Pyle, D. Business Modelling and Data Mining. California: Morgan Kaufmann Publishers. 2003. 650 p.
  24. Pyle, D. Data Preparation for Data Mining. California: Morgan Kaufmann Publishers. 1999. 540 p.
  25. Sładkowski, A. (ed.) Actual problems of logistics. Gliwice: Politechnika Śląska. 2012. 216 p.
  26. Ratner, B. Statistical Modelling and Analysis for Database Marketing: Effective Techniques for Mining Big Data. CRC Press. 2004. 384 p.
  27. Snyder, R.D. & Hyndman, R. & Koehler, A.B. & Ord, J.K. Forecasting with Exponential Smoothing: The State Space Approach. New York: Springer Science & Business Media. 2008. 362 p.
  28. Stopka, O. & Kampf, R. & Kolář, J. & Kubašáková, I. Identification of Appropriate Methods for Allocation Tasks of Logistics Objects in a Certain Area. Our Sea. International Journal of Maritime Science & Technology. Vol.61. No.1-2, May 2014. P. 1-6.
  29. Seidman, C. Data Mining with Microsoft® SQL ServerTM 2000 Technical Reference. Microsoft Press. 2010. 384 p.
  30. Smejkal, V. Řízení rizik ve firmách a jiných organizacích - 3., rozšířené a aktualizované vydání. Praha: Grada Publishing a.s.2010. 354 p. [In Check: Smejkal, V. Risk management in companies and other organizations - 3rd, expanded and updated edition. Prague: Grada Publishing Inc] 
  31. STATISTICA ve vašem městě: sborník k cyklu prezentací nové generace programů, podzim 2001: nová generace 6. Praha: StatSoft. 2001. 128 p. [In Check: STATISTICA in your city: Proceedings to series of presentations of the new generation of programs in autumn 2001: a new generation of 6th. Prague: StatSoft].
  32. Jones, M.T. Artificial Intelligence: A Systems Approach. Burlington: Jones & Bartlett Learning. 2009. 498 p.
  33. Mills, T.C. Time Series Techniques for Economists. Cambridge: Cambridge University Press. 1991. 377 p.
  34. Volná, E. Neuronové sítě 1. Ostrava: Ostravská univerzita v Ostravě. Vydání: druhé. 2008. 86 p. Available at: http://www1.osu.cz/~volna/Neuronove_site_skripta.pdf [In Czech: Volná, E. Neural network 1. Ostrava: University of Ostrava, Issue Secondly].
  35. Volná, E. Evoluční algoritmy a neuronové sítě. Ostrava: Ostravská univerzita v Ostravě. 2013. Available at: http://www1.osu.cz/~volna/Evolucni_algoritmy_a_neuronove_site.pdf. [In Czech: Volná, E. Neural network 1. Ostrava: University of Ostrava, Issue Secondly]
  36. Český statistický úřad. Dostupné z: www.czso.cz. [In Check: The Czech Statistical Office. Available at: www.czso.cz].

EXTRA FILES

COMMENTS