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    Travel mode choice: a data fusion model using machine learning methods and evidence from travel diary survey data

    Chang, Ximing / Wu, Jianjun / Liu, Hao et al. | Taylor & Francis Verlag | 2019
    Schlagwörter: machine learning

    Forecasting road traffic conditions using a context-based random forest algorithm

    Evans, Jonny / Waterson, Ben / Hamilton, Andrew | Taylor & Francis Verlag | 2019
    Schlagwörter: machine learning

    Asynchronous n-step Q-learning adaptive traffic signal control

    Genders, Wade / Razavi, Saiedeh | Taylor & Francis Verlag | 2019
    Schlagwörter: reinforcement learning

    Investigating an SVM-driven, one-class approach to estimating ship systems condition

    Lazakis, Iraklis / Gkerekos, Christos / Theotokatos, Gerasimos | Taylor & Francis Verlag | 2019
    Schlagwörter: machine learning

    Short-term traffic flow prediction based on spatio-temporal analysis and CNN deep learning

    Zhang, Weibin / Yu, Yinghao / Qi, Yong et al. | Taylor & Francis Verlag | 2019
    Schlagwörter: deep learning

    Equality of public transit connectivity: the influence of mass rapid transit services on individual buildings for Singapore

    Li, Zengxiang / Ren, Shen / Hu, Nan et al. | Taylor & Francis Verlag | 2019
    Schlagwörter: machine learning

    PCA-based missing information imputation for real-time crash likelihood prediction under imbalanced data

    Ke, Jintao / Zhang, Shuaichao / Yang, Hai et al. | Taylor & Francis Verlag | 2019
    Schlagwörter: cost-sensitive learning

    Trajectory tracking for autonomous vehicles on varying road surfaces by friction-adaptive nonlinear model predictive control

    Berntorp, K. / Quirynen, R. / Uno, T. et al. | Taylor & Francis Verlag | 2020
    Schlagwörter: parameter learning

    Network-wide traffic signal control based on the discovery of critical nodes and deep reinforcement learning

    Xu, Ming / Wu, Jianping / Huang, Ling et al. | Taylor & Francis Verlag | 2020
    Schlagwörter: deep reinforcement learning

    Short-term metro passenger flow forecasting using ensemble-chaos support vector regression

    Shi, Zhuangbin / Zhang, Ning / Schonfeld, Paul M. et al. | Taylor & Francis Verlag | 2020
    Schlagwörter: ensemble learning

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