[1] YANG C H. Research on construction of digital Intelligent city management system[J]. International Journal of Hybrid Information Technology, 2014,7(5):285-294.
[2] ZHAO D B, DAI Y J, ZHANG Z. Computational intelligence in urban traffic signal control: A survey[J]. IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, 2012,42(4):485-494.
[3] ZHANG L D, ZHU W X. Delay-feedback control strategy for reducing[J]. Physica A: Statistical Mechanics and Its Applications, 2015,428:481-492.
[4] HUANG Y S, WENG Y S, ZHOU M C. Design of regulatory traffic light control systems with synchronized timed Petri nets[J]. Asian Journal of Control, 2018,20(5):174-185.
[5] COLLOTTA M, PAU G. New solutions based on wireless networks for dynamic traffic lights management: A comparison between IEEE 802.15.4 and Bluetooth[J]. Transport and Telecommunication Journal, 2015,16(3):224-236.
[6] LEAL S S, DE ALMEIDA P E M, CHUNG E. Active control for traffic lights in regions and corridors: An approach based on evolutionary computation[J]. Transportation Research Procedia, 2017,25:1769-1780.
[7] 吴黎兵,聂雷,刘冰艺,等. 一种VANET环境下的智能交通信号控制方法[J]. 计算机学报, 2016,39(6):1105-1119.
[8] COOPER B G F, HERSOVITS E. A Bayesian method for the induction of probabilistic networks from data[J]. Machine Learning, 1992,9(4):309-347.
[9] ROCCHETTA R, BROGGI M, HUCHET Q, et al. On-line Bayesian model updating for structural health monitoring[J]. Mechanical Systems and Signal Processing, 2018,103(3):174-195.
[10]陈龙,马亚平. 基于分层贝叶斯网络的航母编队对潜威胁评估[J]. 系统仿真学报, 2017,29(9):2206-2212.
[11]邢志伟,蒋骏贤,罗晓,等. 基于贝叶斯网的离港航班滑行时间动态估计[J]. 计算机工程与应用, 2018,54(24):66-71.
[12]惠飞,穆柯楠,赵祥模. 基于动态概率网格和贝叶斯决策网络的车辆变道辅助驾驶决策方法[J]. 交通运输工程学报, 2018,18(2):148-158.
[13]吕学志,胡晓峰,吴琳,等. 基于贝叶斯网络的任务共同体识别[J]. 计算机工程与应用, 2019,55(5):251-257.
[14]KOLLER D, FRIEDMAN N. Probabilistic Graphical Models[M]. Cambridge, MIT Press, 2009:184-201.
[15]FIREDMAN N, GEIGER D, GOLDSZMIDT M. Bayesian network classifiers[J]. Machine Learning, 1997,29(2/3):131-163.
[16]张连文,郭海鹏. 贝叶斯网引论[M]. 北京:科学出版社, 2006:61-62.
[17]齐伟钢,彭凝多,黄慧萍. 基于静态贝叶斯博弈的SCADA系统安防策略选择[J]. 通信技术, 2017,50(9):2037-2044.
[18]仝兆景,张艳杰,赵运星,等. 基于动态贝叶斯网络的装甲车辆前向防撞预警模型[J]. 制造业自动化, 2019,41(2):114-116.
[19]李文广,孙世宇,李建增,等. 无人机航迹规划中动态威胁评估方法[J]. 火力与指挥控制, 2019,44(2):50-53.
[20]戴志辉,谢军,陈曦,等. 基于动态贝叶斯网络的智能变电站监控系统可靠性分析[J]. 电力系统保护与控制, 2018,46(23):68-76.
[21]RUSSELL S J, NORVIG P. Artificial Intelligence: A Modern Approach[M]. Prentice Hall, 1995.
[22]CHEN H Y, NIE H Y, MAO R R. A new inference of dynamic Bayesian networks: Forwards-backwards algorithm based on sliding window[J]. Journal of Computational Information Systems, 2015,11(9):3371-3378.
[23]GAO X G, MEI J F, CHEN H Y, et al. Approximate inference for dynamic Bayesian networks: Sliding window approach[J]. Applied Intelligence, 2014,40(4):575-591. |