Real-time multistep prediction of public parking spaces based on Fourier transform–least squares support vector regression

References

• Adankon, M. M., & Cheriet, M. (2009). Model selection for the LS-SVM. application to handwriting recognition. Pattern Recognition, 42(12), 3264–3270. doi:10.1016/j.patcog.2008.10.023
   Web of Science ®Google Scholar
• Cai, Z., Sun, J. Modified C0 complexity and applications. (2008). Journal of Fudan University (Natural Science Edition), 47(6), 791–796.
   Google Scholar
• Caliskan, M., Barthels, A., Scheuermann, B., & Mauve, M. (2007). Predicting parking lot occupancy in vehicular ad hoc networks. IEEE Vehicular Technology Conference. IEEE. Retrieved from https://ieeexplore.ieee.org/document/4212497
   Google Scholar
• Chai, H., Ma, R., & Zhang, H. M. (2018). Search for parking: A dynamic parking and route guidance system for efficient parking and traffic management. Journal of Intelligent Transportation Systems, 1–16. doi:10.1080/15472450.2018.1488218
   Web of Science ®Google Scholar
• Guo, W., Zhang, Y., Xu, M., Zhang, Z., & Li, L. (2016). Parking spaces repurchase strategy design via simulation optimization. Journal of Intelligent Transportation Systems, 20(3), 255–269. doi:10.1080/15472450.2015.1063424
   Web of Science ®Google Scholar
• Haisheng, L., Long, L., Li, C., Cheng, L., & Qiang, C. (2015). The prediction in computer color matching of dentistry based on ga + bp neural network. Computational and Mathematical Methods in Medicine, 2015, 1–7. doi:10.1155/2015/816719
   Google Scholar
• Inaba, K., Shibui, M., Naganawa, T., Ogiwara, M., & Yoshikai, N. (2001). Intelligent parking reservation service on the Internet. Applications and the Internet Workshops, 2001. Proceedings. 2001 Symposium on IEEE. Retrieved from https://ieeexplore.ieee.org/document/998224
   Google Scholar
• Ji, Y. (2007). Available parking space occupancy change characteristics and short-term forecasting model. Journal of Southeast University, 23(4), 604–608.
   Google Scholar
• Ji, Y., Tang, D., Blythe, P., & Guo, W. (2015). Short-term forecasting of available parking space using wavelet neural network model. Intelligent Transport Systems, 9(2), 202–209. doi:10.1049/iet-its.2013.0184
   Google Scholar
• Ji, Y. J., Tang, D. N., Guo, W. H., Blythe, P. T., & Wang, W. (2014). Forecasting available parking space with largest Lyapunov exponents method. Journal of Central South University, 21(4), 1624–1632. doi:10.1007/s11771-014-2104-3
   Web of Science ®Google Scholar
• Klappenecker, A., Lee, H., & Welch, J. L. (2014). Finding available parking spaces made easy. Ad Hoc Networks, 12(1), 243–249. doi:10.1016/j.adhoc.2012.03.002
   Google Scholar
• Li, D. C., Wen, I. H., & Chang, C. C. (2014). A new virtual-sample-generating method based on the heuristics algorithm. IEEE International Conference on Grey Systems & Intelligent Services. IEEE. Retrieved from https://ieeexplore.ieee.org/document/6714829
   Google Scholar
• Liu, W., Yang, H., & Yin, Y. (2014). Expirable parking reservations for managing morning commute with parking space constraints. Transportation Research Part C: Emerging Technologies, 44, 185–201. doi:10.1016/j.trc.2014.04.002
   Web of Science ®Google Scholar
• Majidi, A., Polat, H., & Çetin, A. (2016). Finding a best parking place using exponential smoothing and cloud system in a metropolitan area. In Smart Grid Congress & Fair. IEEE. Retrieved from https://ieeexplore.ieee.org/document/7492439
   Google Scholar
• Mei, Z., Feng, C., Ding, W., Zhang, L., & Wang, D. (2019). Better lucky than rich? Comparative analysis of parking reservation and parking charge. Transport Policy, 75(3), 47–56. doi:10.1016/j.tranpol.2019.01.001
   Web of Science ®Google Scholar
• Shoup, D. (2017). The high cost of free parking: Updated edition. Routledge. Retrieved from https://doi.org/10.4324/9781351179782
   Google Scholar
• Suykens, J. A., Van Gestel, T., & De Brabanter, J. (2002). Least Squares Support Vector Machines, World scientific. doi:10.1142/5089
   Google Scholar
• Saunders, C., Gammerman, A., & Vovk, V. (1998). Ridge regression learning algorithm in dual variables. International Conference on Machine Learning. Retrieved from https://eprints.soton.ac.uk/258942/
   Google Scholar
• Suykens, J. A. K., & Vandewalle, J. (1999). Least squares support vector machine classifiers. Neural Processing Letters, 9(3), 293–300.
   Web of Science ®Google Scholar
• Thompson, R. G., Takada, K., & Kobayakawa, S. (2001). Optimisation of parking guidance and information systems display configurations. Transportation Research Part C (Emerging Technologies), 9(1), 69–85. doi:10.1016/S0968-090X(00)00031-0
   Web of Science ®Google Scholar
• Taieb, S. B., & Atiya, A. F. (2016). A bias and variance analysis for multistep-ahead time series forecasting. IEEE Transactions on Neural Networks and Learning Systems, 27(1), 62–76. doi:10.1109/TNNLS.2015.2411629
   PubMed Web of Science ®Google Scholar
• Vapnik, V. (1995). The nature of statistical learning theory. Springer. Retrieved from https://link.springer.com/book/10.1007%2F978-1-4757-2440-0
   Google Scholar
• Van Gestel, T., Suykens, J. A. K., De Moor, B., & Vandewalle, J. (2001a). Automatic relevance determination for least squares support vector machine regression. In Neural Networks, 2001. Proceedings. IJCNN'01. International Joint Conference on (Vol. 4, pp. 2416-2421). IEEE. Retrieved from https://ieeexplore.ieee.org/document/938745
   Google Scholar
• Van Gestel, T., Suykens, J. A. K., Baestaens, D.-E., Lambrechts, A., Lanckriet, G., Vandaele, B., … Vandewalle, J. (2001b). Financial time series prediction using least squares support vector machines within the evidence framework. IEEE Transactions on Neural Networks, 12(4), 809–821. doi:10.1109/72.935093
   PubMed Web of Science ®Google Scholar
• Vlahogianni, E. I., Kepaptsoglou, K., Tsetsos, V., & Karlaftis, M. G. (2016). A real-time parking prediction system for smart cities. Journal of Intelligent Transportation Systems, 20(2), 192–204. doi:10.1080/15472450.2015.1037955
   Web of Science ®Google Scholar
• Yong, S., Chunping, L., Yihuai, W., Shukui, Z., & Feixiong, L. (2009). A forecasting model for parking guidance system. In 2009 World Congress on Computer Science and Information Engineering (vol. 3, pp. 607–611). IEEE.
   Google Scholar
• Zheng, Y., Rajasegarar, S., & Leckie, C. (2015). Parking availability prediction for sensor-enabled car parks in smart cities. In Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2015 IEEE Tenth International Conference on (pp. 1–6). IEEE. Retrieved from https://ieeexplore.ieee.org/document/938745
   Google Scholar