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A Simple Classification Approach to Traffic Flow State Estimation

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Computer Aided Systems Theory – EUROCAST 2017 (EUROCAST 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10672))

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Abstract

One of the most important elements in the mobility of the developed cities is the road traffic management. The mobility determines the quality of citizens’ living conditions because of many reasons, security, efficiency, and the environmental impact. Focusing on security, according to World Health Organization (WHO), every year two millions of people die as a result of traffic accidents. Moreover between twenty and fifty millions of people suffer non-fatal injuries and a proportion of these people suffer from a disability. These injuries affect both the family economy and the country. For this reason, amongst others, it is required to equip the mobility managers with the proper tools to get a precise idea about the current situation and estimate future state. These tools facilitate the decision-making and the development of mobility.

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References

  1. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. Al Magazine 17(3), 37–54 (1996)

    Google Scholar 

  2. Moreira-Matias, L.: Taxi service trajectory, prediction challenge (2015). https://archive.ics.uci.edu/ml/datasets/Taxi+Service+Trajectory+-+Prediction+Challenge,+ECML+PKDD+2015

  3. Maerivoet, S., Moor, B.D.: Traffic flow theory (2008)

    Google Scholar 

  4. Arbaiza, A., Martínez, P.T.: Parámetros fundamentales del tráfico ii. la velocidad. definiciones. percentil 85. velocidad inadecuada y velocidad excesiva. otras variables derivadas. métodos de obtención de datos de los parámetros de tráfico. procedimiento de integración y análisis (2014)

    Google Scholar 

  5. Han, J., Kamber, M.: Data Mining: Concepts and Techniques, 2nd edn, chap. 6, pp. 366–367. Morgan Kaufmann Publishers, Los Altos (2006)

    Google Scholar 

  6. Data Mining: Concepts and Techniques, 2nd edn, chap. 8, pp. 482–484. Morgan Kaufmann Publishers, Los Altos (2006)

    Google Scholar 

  7. Breiman, L.: Machine Learning, pp. 5–32. Kluwer Academic Publishers, Dordrecht (2001)

    Google Scholar 

  8. Divya, M., Vijayarani, S.: An efficient algorithm for classification rule hiding. 33(3) (2011)

    Google Scholar 

  9. Tang, K., Wang, R., Chen, T.: Towards maximizing the area under the ROC curve for multi-class classification problems

    Google Scholar 

  10. Witten, I.H., Frank, E., Hall, M.A.: Data Mining Practical Machine Learning Tools and Techniques, 3rd edn, chap. 9, pp. 380–383. Morgan Kaufmann Publishers, Los Altos (2011)

    Google Scholar 

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Correspondence to Javier J. Sánchez Medina .

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del Pino Saavedra Hernández, A., Sánchez Medina, J.J., Moraine-Matias, L. (2018). A Simple Classification Approach to Traffic Flow State Estimation. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2017. EUROCAST 2017. Lecture Notes in Computer Science(), vol 10672. Springer, Cham. https://doi.org/10.1007/978-3-319-74727-9_52

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  • DOI: https://doi.org/10.1007/978-3-319-74727-9_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74726-2

  • Online ISBN: 978-3-319-74727-9

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