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Synonyme wurden verwendet für: RF • forest • model
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    Understanding drivers' route choice behaviours in the urban network with machine learning models

    Freier Zugriff
    Lai, Xinjun / Fu, Hui / Li, Jun et al. | IET | 2018
    Schlagwörter: random utility models , traditional models , random processes , ML models , machine learning models , random forest

    Real-time crash prediction on urban expressways: identification of key variables and a hybrid support vector machine model

    Freier Zugriff
    Sun, Jie / Sun, Jian | IET | 2016
    Schlagwörter: hybrid support vector machine model , hybrid SVM model , random forest model , RF model

    Dynamic pricing strategy for high occupancy toll lanes based on random forest and nested model

    Freier Zugriff
    Zhang, Kai / Zhou, Zhuping / Qi, Yong et al. | IET | 2018
    Schlagwörter: nested model , random forest method , random processes , lane choice behaviour prediction model , RF

    Identifying commuters based on random forest of smartcard data

    Freier Zugriff
    Mei, Zhenyu / Ding, Wenchao / Feng, Chi et al. | IET | 2020
    Schlagwörter: random forest algorithm , personal-level commute models , validated random forest model

    Efficient deep learning based method for multi-lane speed forecasting: a case study in Beijing

    Freier Zugriff
    Lu, Wenqi / Yi, Ziwei / Liu, Wan et al. | IET | 2021
    Schlagwörter: RF-CWRNN method , random forests , random forest

    Hybrid data-driven approach for truck travel time imputation

    Freier Zugriff
    Karimpour, Abolfazl / Ariannezhad, Amin / Wu, Yao-Jan | IET | 2019
    Schlagwörter: hybrid model , popular imputation models , random forest

    Seoul bike trip duration prediction using data mining techniques

    Freier Zugriff
    V E, Sathishkumar / Park, Jangwoo / Cho, Yongyun | IET | 2020
    Schlagwörter: random forests , statistical models , Random Forest

    Vehicle detection, counting and classification in various conditions

    Freier Zugriff
    Kamkar, Shiva / Safabakhsh, Reza | IET | 2016
    Schlagwörter: random forest , active basis model

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