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3770 Journal of Software 软件学报 Vol.31, No.12, December 2020

[68] Krizhevsky A, Sutskever I, Hinton G. ImageNet classification with deep convolutional neural networks. In: Proc. of the Int’l Conf.
on Neural Information Processing Systems. 2012. 1097−1105.
[69] Erb M, Aertsen A. Dynamics of Activity in Biology-Oriented Neural Network Models: Stability at Low Firing Rates. 1992.
201−223.
[70] Samant A, Adeli H. Enhancing neural network traffic incident-detection algorithms using wavelets. Computer-Aided Civil and
Infrastructure Engineering, 2002,16(4):239−245.
[71] Park D, Rilett LR. Forecasting freeway link travel times with a multilayer feedforward neural network. Computer-Aided Civil and
Infrastructure Engineering, 2010,14(5):357−367.
[72] Chen D, Zhang K, Liao T. Practical travel time prediction algorithms based on neural network and data fusion for urban
expressway. In: Proc. of the 6th Int’l Conf. on Natural Computation. 2010. 1754−1758.
[73] Yun SY, Namkoong S, Rho JH, Shin SW, Choi JU. A performance evaluation of neural network models in traffic volume
forecasting. Mathematical and Computer Modelling, 1998,27(9-11):293−310.
[74] Wan EA. Modeling nonlinear dynamics with neural networks: Examples in time series prediction. In: Proc. of SPIE, 1993.
327−232.
[75] Abdulhai B, Porwal H, Recker W. Short Term Freeway Traffic Flow Prediction Using Genetically-Optimized Time-Delay-Based
Neural Networks. 1999.
[76] Dia H. An object-oriented neural network approach to short-term traffic forecasting. European Journal of Operational Research,
2001,131(2):253−261.
[77] Duan Y, Lv Y, Wang FY. Travel time prediction with LSTM neural network. In: Proc. of the IEEE Int’l Conf. on Intelligent
Transportation Systems. 2016. 1053−1058.
[78] Wang FY, Duan YJ, Lv YS, Chen YY, Lin YL, Liu YL. One kind of link travel time forecasting method based on the lstm. Patent
CN106096767A, 2016 (in Chinese).
[79] Liu Y, Wang Y, Yang X, Zhang L. Short-Term travel time prediction by deep learning: A comparison of different LSTM-DNN
models. In: Proc. of the IEEE Int’l Conf. on Intelligent Transportation Systems. 2017. 1−8.
[80] J Lint JWCV, Hoogendoorn SP, Zuylen HJV. Accurate travel time prediction with state-space neural networks under missing data.
Transportation Research Part C Emerging Technologies, 2005,13(s 5-6):347−369.
[81] Li X, Wang C, Shi H. A travel time prediction method: Bayesian reasoning state-space neural network. In: Proc. of the 2010 2nd
Int’l Conf. on Information Science and Engineering (ICISE). 2010. 936−940.
[82] Vapnik V. The nature of statistical learning theory. Technometrics, 1995,38(4):409−409.
[83] Wu CH, Ho JM, Lee DT. Travel-Time prediction with support vector regression. IEEE Trans. on Intelligent Transportation Systems,
2004,5(4):276−281.
[84] Castro-Neto M, Jeong YS, Jeong MK, Han LD. Online-SVR for short-term traffic flow prediction under typical and atypical traffic
conditions. Expert Systems with Applications, 2009,36(3):6164−6173.
[85] Gao P, Hu J, Zhou H, Zhang Y. Travel time prediction with immune genetic algorithm and support vector regression. In: Proc. of
the World Congress on Intelligent Control and Automation. 2016. 987−992.
[86] Tan GZ, Zhou DM, Jiang B, Dioubate MI. Elitism-Based immune genetic algorithm and its application to optimization of complex
multi-modal functions. Journal of Central South University of Technology, 2008,15(6):845−852.
[87] Smith BL, Williams BM, Oswald RK. Comparison of parametric and nonparametric models for traffic flow forecasting.
Transportation Research Part C (Emerging Technologies), 2002,10(4):303−321.
[88] Bajwa SI, Chung E, Kuwahara M. Performance evaluation of an adaptive travel time prediction model. In: Proc. of the IEEE
Intelligent Transportation Systems. 2005. 1000−1005.
[89] Lim S, Lee C. Data fusion algorithm improves travel time predictions. IET Intelligent Transport Systems, 2011,5(4):302−309.
[90] Wang JY, Wong KI, Chen YY. Short-Term travel time estimation and prediction for long freeway corridor using NN and
regression. In: Proc. of the Int’l IEEE Conf. on Intelligent Transportation Systems. 2012. 582−587.
[91] Tak S, Kim S, Oh S, Yeo H. Development of a data-driven framework for RealTime travel time prediction. Computer-Aided Civil
and Infrastructure Engineering, 2016,31(10):777−793.