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    A reinforcement learning model for personalized driving policies identification

    Freier Zugriff
    Dimitris M. Vlachogiannis / Eleni I. Vlahogianni / John Golias | DOAJ | 2020
    Schlagwörter: Reinforcement learning , Q-learning , Machine learning

    Learning through policy transfer? Reviewing a decade of scholarship for the field of transport

    Freier Zugriff
    Glaser, Meredith / Bertolini, Luca / te Brömmelstroet, Marco et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: policy learning , learning

    Planning maintenance and rehabilitation activities for airport pavements: A combined supervised machine learning and reinforcement learning approach

    Freier Zugriff
    Limon Barua / Bo Zou | DOAJ | 2022
    Schlagwörter: Reinforcement learning , Q-learning

    Traffic volume prediction on low-volume roadways: a Cubist approach

    Das, Subasish | Taylor & Francis Verlag | 2021
    Schlagwörter: machine learning

    An interpretable machine learning framework to understand bikeshare demand before and during the COVID-19 pandemic in New York City

    Uddin, Majbah / Hwang, Ho-Ling / Hasnine, Md Sami | Taylor & Francis Verlag | 2023
    Schlagwörter: machine learning

    A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis

    Freier Zugriff
    Rawson, Andrew / Brito, Mario | Taylor & Francis Verlag | 2023
    Schlagwörter: Machine learning

    Development of a global road safety performance function using deep neural networks

    Freier Zugriff
    Guangyuan Pan / Liping Fu / Lalita Thakali | DOAJ | 2017
    Schlagwörter: Deep learning

    Consumer learning behavior in choosing electric motorcycles

    Sung, Yen-Ching | Taylor & Francis Verlag | 2010
    Schlagwörter: Bayesian learning

    Development of LSTM-MLR hybrid model for radar detector missing and outlier traffic volume correction

    Kim, Dohoon / Kim, Eungcheol | Taylor & Francis Verlag | 2023
    Schlagwörter: deep-learning

    Analyzing injury severity of motorcycle at-fault crashes using machine learning techniques, decision tree and logistic regression models

    Freier Zugriff
    Mahdi Rezapour / Amirarsalan Mehrara Molan / Khaled Ksaibati | DOAJ | 2020
    Schlagwörter: Machine learning techniques

    Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

    Uddin, Majbah / Anowar, Sabreena / Eluru, Naveen | Taylor & Francis Verlag | 2021
    Schlagwörter: machine learning

    Using supervised machine learning algorithms in pavement degradation monitoring

    Freier Zugriff
    Amir Shtayat / Sara Moridpour / Berthold Best et al. | DOAJ | 2023
    Schlagwörter: Machine Learning

    Applications of machine learning methods in traffic crash severity modelling: current status and future directions

    Wen, Xiao / Xie, Yuanchang / Jiang, Liming et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: machine learning

    Automatic topics extraction from crowdsourced cyclists near-miss and collision reports using text mining and Artificial Neural Networks

    Freier Zugriff
    Keneth Morgan Kwayu / Valerian Kwigizile / Kevin Lee et al. | DOAJ | 2022
    Schlagwörter: Machine learning

    Integrating built environment and parking policy for car commuting reduction: evidence from Beijing

    Wang, Xiaoquan / Yin, Chaoying / Zheng, Changjiang et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: machine learning model

    Analyzing travel behavior in Hanoi using Support Vector Machine

    Truong, Thi My Thanh / Ly, Hai-Bang / Lee, Dongwoo et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: Machine Learning

    Investigating pedestrian crash patterns at high-speed intersection and road segments: Findings from the unsupervised learning algorithm

    Freier Zugriff
    Ahmed Hossain / Xiaoduan Sun / Niaz Mahmud Zafri et al. | DOAJ | 2024
    Schlagwörter: Unsupervised learning

    Deep hybrid learning framework for spatiotemporal crash prediction using big traffic data

    Freier Zugriff
    Mohammad Tamim Kashifi / Mohammed Al-Turki / Abdul Wakil Sharify | DOAJ | 2023
    Schlagwörter: Deep Hybrid Learning

    A state-of-the-art survey of deep learning models for automated pavement crack segmentation

    Freier Zugriff
    Hongren Gong / Liming Liu / Haimei Liang et al. | DOAJ | 2024
    Schlagwörter: Deep learning

    Application of machine learning models to predict driver left turn destination lane choice behavior at urban intersections

    Freier Zugriff
    Mohammed Moinuddin / Logan Proffer / Matthew Vechione et al. | DOAJ | 2024
    Schlagwörter: Applied Machine Learning