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Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine

by K.b. Priya Iyer, V. Shanthi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 15
Year of Publication: 2012
Authors: K.b. Priya Iyer, V. Shanthi
10.5120/6859-9489

K.b. Priya Iyer, V. Shanthi . Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine. International Journal of Computer Applications. 45, 15 ( May 2012), 52-58. DOI=10.5120/6859-9489

@article{ 10.5120/6859-9489,
author = { K.b. Priya Iyer, V. Shanthi },
title = { Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 15 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 52-58 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number15/6859-9489/ },
doi = { 10.5120/6859-9489 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:37:42.567283+05:30
%A K.b. Priya Iyer
%A V. Shanthi
%T Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 15
%P 52-58
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Embedding Information technology with Transportation system creates a new era in building Intelligent Transportation System (ITS). An effective Intelligent Transportation System reduces traffic congestion, environmental pollution, fuel consumption and driver in-convenience etc. The widespread adoption of GPS-enabled mobile devices has opened new possibilities of developing an ITS. With advancements in Wireless technologies, GIS and sensors, spatial route search are important class of queries under location based services. In this paper, we introduce a new spatial query called Predictive Skyline query (PSQ) on time dependent road networks. The PSQ is a spatial route search query for future journey schedule which are popular apps under Intelligent Transportation Systems. The algorithm consists of five phases namely PSQuery Initiator (QI), Fuzzy Travel Time Forecaster (FTF), PSQuery Executor and Optimizer (QEO), Traffic Fuzzy Controller (TFC), PSQuery Recorder (QR). The FTF predicts the travel time based on historical data using fuzzy inference rules. The TFC predicts the overall traffic congestion in the user specified spatial region on the scheduled journey date. The experimental evaluation reflects the accuracy of travel time prediction in real road networks and efficiency of algorithm in processing PSQ queries.

References
  1. B. Bartin and K. Ozbay. 2010. Determining the optimal configuration of highway routes for real-time traffic information: A case study. IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 1, pp. 225–231.
  2. S. Borzsonyi, D. Kossmann, and K. Stoker. 2001. The skyline operator. ICDE.
  3. K. Deng, X. Zhou, and H. T. Shen. 2007. Multi-source skyline query processing in road networks. In Proc. 23th Int. Conf. on Data Engineering, pages 796–805.
  4. Hui Zhu Su, En Tzu Wang and Arbee L. P. Chen. 2011. Continuous probabilistic skyline queries over uncertain data streams. Database and Expert Systems Applications, Springer.
  5. Khodayari A, Kazemi R, Ghaffari A,Braunstingl R. 2011. Design of an improved fuzzy logic based model for prediction of car following behavior. IEEE International Conference on Mechatronics (ICM), On Page(s): 200 – 205.
  6. D. Kossmann, F. Ranmsak, and S. Rost. 2002. Shooting stars in the sky: An online algorithm for skyline queries. VLDB.
  7. Kriegel, H. -P. ; Renz, M. ; Schubert, M. 2010. Route skyline queries: A multi-preference path planning approach. in IEEE 26th International Conference on Data Engineering (ICDE).
  8. X. Lin, Y. Yuan, W. Wang, and H. Lu. 2005. Stabbing the sky: Efficient skyline computation over sliding windows. ICDE.
  9. E. Mazloumi, G. Currie, and G. Rose. 2010. Using GPS data to gain insight into public transport travel time variability," Journal of Transportation Engineering, vol. 136, no. 7, pp. 623–631.
  10. E. Mazloumi, G. Rose, G. Currie, and S. Moridpour. 2010. Prediction intervals to account for uncertainties in neural network predictions: Methodology and application in bus travel time prediction, Engineering Applications of Artificial Intelligence.
  11. Mehdi Sharifzadeh, Cyrus Shahabi, and Leyla Kazemi. 2009. Processing spatial skyline queries in both vector spaces and spatial network databases, ACM Transactions on Database Systems, vol. 34, no. 3,pp. 1-43.
  12. D. Papadias, Y. Tao, G. Fu, and B. Seeger. 2005. Progressive skyline computation in database systems. ACM Trans. Database Syst. , 30(1):41–82.
  13. J. Pei, B. Jiang, X. Lin, and Y. Yuan. 2007. Probabilistic skylines on uncertain data. In Proc. 33th Int. Conf. on Very LargeData Bases, pages 15–26.
  14. J. Pei, W. Jin, M. Ester, and Y. Tao. 2005. Catching the best views of skyline: a semantic approach based on decisive subspaces. In Proc. 31th Int. Conf. on Very Large Data Bases, pages 253–264.
  15. M. Sharifzadeh and C. Shahabi. 2006. The spatial skyline queries. VLDB.
  16. Simroth, A. Za?hle, H. Travel Time Prediction Using Floating Car Data Applied to Logistics Planning. IEEE Transactions on Intelligent Transportation Systems, Volume: 12, Issue: 1, On Page(s): 243 – 253.
  17. F. Soriguera F. Robusté. 2011. Highway travel time accurate measurement and short-term prediction using multiple data sources. Transportmetrica, Volume 7, Issue 1, pages 85-109.
  18. Y. Tao, X. K. Xiao, and J. Pei. 2006. SUBSKY: Efficient computation of skylines in subspaces. In Proc. 22th Int. Conf. on Data Engineering, page 65.
  19. M. Yang, Y. Liu, and Z. You. 2010. The reliability of travel time forecasting. IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 1, pp. 162–171.
  20. Y. Yuan, X. Lin, Q. , W. Wang, J. Xu Yu, and Q. Zhang. 2005. Efficient computation of the skyline cube. In Proc. 31th Int. Conf. on Very Large Data Bases.
  21. Tiger/Line: ww. census. gov/geo/www/tiger/.
Index Terms

Computer Science
Information Sciences

Keywords

Predictive Skyline Queries Traffic Congestion Fuzzy Controller Fuzzy Rules Traffic Prediction Spatial Databases Skyline Queries Gis Location Based Services Gps

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