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Improved Traffic Prediction by Applying KNN and Euclidean Distance ARIMA (Ke-Arima) Approach

by Priyanka Rani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 3
Year of Publication: 2018
Authors: Priyanka Rani
10.5120/ijca2018917488

Priyanka Rani . Improved Traffic Prediction by Applying KNN and Euclidean Distance ARIMA (Ke-Arima) Approach. International Journal of Computer Applications. 182, 3 ( Jul 2018), 23-29. DOI=10.5120/ijca2018917488

@article{ 10.5120/ijca2018917488,
author = { Priyanka Rani },
title = { Improved Traffic Prediction by Applying KNN and Euclidean Distance ARIMA (Ke-Arima) Approach },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 182 },
number = { 3 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 23-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number3/29743-2018917488/ },
doi = { 10.5120/ijca2018917488 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:17.158825+05:30
%A Priyanka Rani
%T Improved Traffic Prediction by Applying KNN and Euclidean Distance ARIMA (Ke-Arima) Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 3
%P 23-29
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the modern era, the road infrastructure failed to cope up with the exponential increase of road traffic. There is a thrust to find a smarter way to deal with such transportation system. Intelligent Transport System is at the forefront edge of this, one of the points is exact and hassle-free forecasts that guarantee smooth and bother free driving and authoritative experience. In such manner, Intelligent Transport System (ITS) being looked into for quite a few years and furthermore a field of consistent growth of works and advancement after some time, there is a wealth of writing on traffic expectation. Traffic datasets generated through the application of IOT are operated upon by the existing techniques. Traffic flow analysis is conducted to tackle the issues of traffic forecasting. This paper presents a systematic analysis of previous aggregate work on traffic prediction, highlight the marked changes and presents future directions for research work.

References
  1. W. Min and L. Wynter, “Real-time road traffic prediction with spatio-temporal correlations,” Transp. Res. Part C, vol. 19, no. 4, pp. 606–616, 2011.
  2. S. V. Kumar and L. Vanajakshi, “Short-term traffic flow prediction using seasonal ARIMA model with limited input data,” Eur. Transp. Res. Rev., vol. 7, no. 3, pp. 1–9, 2015.
  3. X. Yu, “Intelligent Urban Traffic Management System Based on Cloud Computing and Internet of Things,” pp. 2169–2172, 2012.
  4. X. Pang, C. Wang, and G. Huang, “A Short-Term Traffic Flow Forecasting Method Based on a Three-Layer K-Nearest Neighbor Non-Parametric Regression Algorithm,” no. July, pp. 200–206, 2016.
  5. O. U. Chinyere, O. O. Francisca, and O. E. Amano, “D ESIGN AND S IMULATION OF AN I NTELLIGENT T RAFFIC,” vol. 1, no. 5, pp. 47–57, 2011.
  6. C. Xiao-feng, S. Zhong-ke, and Z. Kai, “Research on an Intelligent Traffic Signal Controller,” pp. 884–887, 2003.
  7. L. Kdqj, “An Intelligent Traffic Information Service System based on Agent and GIS-T,” 2010.
  8. B. Singh and A. Gupta, “Recent trends in intelligent transportation systems : a review,” vol. 9, no. 2, pp. 30–34, 2015.
  9. H. O. Al-sakran, “Intelligent Traffic Information System Based on Integration of Internet of Things and Agent Technology,” vol. 6, no. 2, pp. 37–43, 2015.
  10. T. Osman, S. S. Psyche, J. M. S. Ferdous, and H. U. Zaman, “Intelligent Traffic Management System for Cross Section of Roads Using Computer Vision,” 2017.
  11. Y. Wang and H. Qi, “Research of Intelligent Transportation System Based on the Internet of Things Frame,” vol. 2012, no. July, pp. 160–166, 2012.
  12. M. Kim and S. Chang, “,” vol. 62, no. 3, pp. 226–234, 2016.
  13. C. U. Scenarios and R. Architecture, “The advantages of IoT and Cloud applied to Smart Cities,” pp. 325–332, 2015.
  14. S. Vasantha Kumar and Lelitha Vanajakshi, “Short-term traffic flow prediction using seasonal ARIMA model with limited input data,” pp. 1–9, 2016.
  15. A. Mathew, F. A. S. A, H. N. Pooja, and A. Verma, “Smart Disease Surveillance Based on Internet of Things ( IoT ),” vol. 4, no. 5, pp. 180–183, 2015.
  16. B. D. Thomas, R. Mcpherson, G. Paul, and J. Irvine, “Consumption of Wi-Fi for IoT Devices,” no. September, pp. 92–100, 2016.
  17. C. Perera, D. S. Talagala, C. H. Liu, S. Member, and J. C. Estrella, “Energy-Efficient Location and Activity-Aware On-Demand Mobile Distributed Sensing Platform for Sensing as a Service in IoT Clouds,” pp. 1–11, 2016.
  18. J. Mohammed, C.-H. Lung, A. Ocneanu, A. Thakral, C. Jones, and A. Adler, “Internet of Things: Remote Patient Monitoring Using Web Services and Cloud Computing,” in 2014 IEEE International Conference on Internet of Things(iThings), and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom), 2014, pp. 256–263.
  19. F. Chen, P. Deng, J. Wan, D. Zhang, A. V Vasilakos, and X. Rong, “Data Mining for the Internet of Things : Literature Review and Challenges,” vol. 2015, no. i, 2015.
  20. Z. Zhou, C. Du, L. Shu, G. Hancke, J. Niu, and H. Ning, “Combining KNN Algorithm and Other Classifiers ,” in 2010 IEEE International Conference on Cognitive Informatics, 2010,pp.800-805.
  21. D. Miorandi, S. Sicari, F. De Pellegrini, and I. Chlamtac, “Ad Hoc Networks Internet of things : Vision , applications and research challenges,” Ad Hoc Networks, vol. 10, no. 7, pp. 1497–1516, 2012.
  22. P. Vaish, R. Bharath, P. Rajalakshmi, and U. B. Desai, “Smartphone Based Automatic Abnormality Detection of Kidney in Ultrasound Images,” 2016.
  23. M. T. Asif, J. Dauwels, C. Y. Goh, A. Oran, E. Fathi, M. Xu, M. M. Dhanya, N. Mitrovic, and P. Jaillet, “Spatial and Temporal Patterns in Large-Scale Traffic Speed Prediction.”
  24. J. He, W. Shen, P. Divakaruni, L. Wynter, and R. Lawrence, “Improving Traffic Prediction with Tweet Semantics,” pp. 1387–1393.
  25. P. Transportu and T. Pamuła, “ROAD TRAFFIC PARAMETERS PREDICTION IN URBAN TRAFFIC MANAGEMENT SYSTEMS USING NEURAL NETWORKS,” Transport, vol. 6, no. 3, pp. 1–6, 2011.
  26. A. A. Shafie, M. H. Ali, F. Hafiz, and R. M. Ali, “SMART VIDEO SURVEILLANCE SYSTEM FOR VEHICLE DETECTION AND TRAFFIC FLOW CONTROL,” vol. 6, no. 4, pp. 469–480, 2011.
  27. B. Pan, U. Demiryurek, and C. Shahabi, “Utilizing Real-World Transportation Data for Accurate Traffic Prediction.”
  28. S. Suhas, V. K. V, M. Katti, A. P. B. V, and C. Naveena, “A Comprehensive Review on Traffic Prediction for Intelligent Transport System,” 2017.
  29. M. Tan, S. C. Wong, J. Xu, Z. Guan, and P. Zhang, “An Aggregation Approach to Short-Term Traffic Flow Prediction,” vol. 10, no. 1, pp. 60–69, 2009.
  30. A. Wibisono, W. Jatmiko, H. A. Wisesa, B. Hardjono, and P. Mursanto, “Knowledge-Based Systems Traffic big data prediction and visualization using Fast Incremental Model Trees-Drift Detection ( FIMT-DD ),” Knowledge-Based Syst., vol. 93, pp. 33–46, 2016.
  31. S. Sun, C. Zhang, and Y. Zhang, “Traffic Flow Forecasting Using a Spatio-temporal Bayesian Network Predictor,” pp. 273–278, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Traffic prediction Traffic Dataset Internet of Things (IOT) Traffic flow traffic forecasting Intelligent Transport System (ITS).

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