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121–140 von 204 Ergebnissen
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    Electric vehicle charging demand forecasting using deep learning model

    Yi, Zhiyan / Liu, Xiaoyue Cathy / Wei, Ran et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Efficient Exploitation of Existing Corporate Knowledge in Conceptual Ship Design

    Erikstad, Stein Ove / NTNU | Taylor & Francis Verlag | 2007
    Schlagwörter: learning

    Eco-driving at signalized intersections: a parameterized reinforcement learning approach

    Jiang, Xia / Zhang, Jian / Li, Dan | Taylor & Francis Verlag | 2023
    Schlagwörter: reinforcement learning

    EasyJet pricing strategy: determinants and developments

    Malighetti, Paolo / Paleari, Stefano / Redondi, Renato | Taylor & Francis Verlag | 2015
    Schlagwörter: demand learning

    Early wheel flat detection: an automatic data-driven wavelet-based approach for railways

    Mosleh, Araliya / Meixedo, Andreia / Ribeiro, Diogo et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: unsupervised learning

    Dual-channel ticketing and pricing strategies in cruise revenue management

    Chen, Kaimin / Jia, Shuai / Wang, Jing et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: reinforcement learning

    DRL-based adaptive signal control for bus priority service under connected vehicle environment

    Zhang, Xinshao / He, Zhaocheng / Zhu, Yiting et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep reinforcement learning

    Driver steering and muscle activity during a lane-change manoeuvre

    Pick, Andrew J. / Cole, David J. | Taylor & Francis Verlag | 2007
    Schlagwörter: Learning

    Driver’s black box: a system for driver risk assessment using machine learning and fuzzy logic

    Yuksel, A. S. / Atmaca, S. | Taylor & Francis Verlag | 2021
    Schlagwörter: machine learning

    DLW-Net model for traffic flow prediction under adverse weather

    Yao, Ronghan / Zhang, Wensong / Long, Meng | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Discovering vehicle usage patterns on the basis of daily mobility profiles derived from floating car data

    Sun, Danyang / Leurent, Fabien / Xie, Xiaoyan | Taylor & Francis Verlag | 2021
    Schlagwörter: machine learning

    Discharge control policy based on density and speed for deep Q-learning adaptive traffic signal

    Ahmed, Muaid Abdulkareem Alnazir / Khoo, Hooi Ling / Ng, Oon-Ee | Taylor & Francis Verlag | 2023
    Schlagwörter: deep Q-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

    Development of a novel engine power model to estimate heavy-duty truck fuel consumption

    Kan, Yuheng / Liu, Hao / Lu, Xiaoyun et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Detection and Classification of Vehicles by Measurement of Road-Pavement Vibration and by Means of Supervised Machine Learning

    Stocker, Markus / Silvonen, Paula / Rönkkö, Mauno et al. | Taylor & Francis Verlag | 2016
    Schlagwörter: Machine Learning

    Detecting transportation modes using smartphone data and GIS information: evaluating alternative algorithms for an integrated smartphone-based travel diary imputation

    Liu, Yicong / Miller, Eric / Habib, Khandker Nurul | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning , tree-based ensemble learning

    Design of Reinforcement Learning Parameters for Seamless Application of Adaptive Traffic Signal Control

    El-Tantawy, Samah / Abdulhai, Baher / Abdelgawad, Hossam | Taylor & Francis Verlag | 2014
    Schlagwörter: Reinforcement Learning , Temporal Difference Learning

    Designing a lightweight 1D convolutional neural network with Bayesian optimization for wheel flat detection using carbody accelerations

    Shi, Dachuan / Ye, Yunguang / Gillwald, Marco et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: machine learning

    Departure time choice behavior in commute problem with stochastic bottleneck capacity: experiments and modeling

    Liu, Qiumin / Lu, Dongxu / Jiang, Rui et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: reinforcement learning model

    Deep reinforcement learning in dynamic positioning control: by rewarding small response of riser angles

    Wang, Fang / Bai, Yong / Bai, Jie et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: Reinforcement learning , Q-learning