Synonyme wurden verwendet für: learning
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1–50 von 129 Ergebnissen
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    Traffic speed prediction for intelligent transportation system based on a deep feature fusion model

    Li, Linchao / Qu, Xu / Zhang, Jian et al. | Taylor & Francis Verlag | 2019
    Schlagwörter: deep learning , machine 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

    Phi-Net: Deep Residual Learning for InSAR Parameters Estimation

    Freier Zugriff
    Sica, Francescopaolo / Gobbi, Giorgia / Rizzoli, Paola et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2020
    Schlagwörter: Residual Learning , Deep Learning

    Using reinforcement learning to minimize taxi idle times

    O’Keeffe, Kevin / Anklesaria, Sam / Santi, Paolo et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning , reinforcement learning

    Les réseaux apprennants à la SNCF ou comment rendre les organisations vivante

    Raynard, Thierry | IuD Bahn | 2014
    Schlagwörter: Betriebliches Lernen

    Online longitudinal trajectory planning for connected and autonomous vehicles in mixed traffic flow with deep reinforcement learning approach

    Cheng, Yanqiu / Hu, Xianbiao / Chen, Kuanmin et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep Q-learning , reinforcement learning

    A cold-start-free reinforcement learning approach for traffic signal control

    Xiao, Nan / Yu, Liang / Yu, Jinqiang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning , reinforcement learning

    A CNN-Based Coherence-Driven Approach for InSAR Phase Unwrapping

    Freier Zugriff
    Sica, Francescopaolo / Calvanese, Francesco / Scarpa, Giuseppe et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2020
    Schlagwörter: Deep Learning

    Deep Q learning-based traffic signal control algorithms: Model development and evaluation with field data

    Wang, Hao / Yuan, Yun / Yang, Xianfeng Terry et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep reinforcement learning , Q-learning

    Artificial intelligence for traffic signal control based solely on video images

    Jeon, Hyunjeong / Lee, Jincheol / Sohn, Keemin | Taylor & Francis Verlag | 2018
    Schlagwörter: deep learning , reinforcement learning (RL)

    Considerazioni sulla formazione mediante simulatori di condotta

    Capaccioli, Tanya | IuD Bahn | 2006
    Schlagwörter: Betriebliches Lernen

    Ausbilden auf hohem Niveau

    Komplexer Lernstoff lässt sich in Blended-Learning-Modulen aufbereiten
    Hofmann, Ursula | IuD Bahn | 2004
    Schlagwörter: Betriebliches Lernen

    Iterative Learning Control Algorithm for Feedforward Controller of EGR and VGT Systems in a CRDI Diesel Engine

    Min, Kyunghan / Sunwoo, Myoungho / Han, Manbae | Springer Verlag | 2018
    Schlagwörter: Learning control , Iterative learning control

    Machine learning algorithms in ship design optimization

    Peri, Daniele | Taylor & Francis Verlag | 2024
    Schlagwörter: machine learning

    Lerntypen

    Mit einer typengerechten Gestaltung zum optimalen Lernerfolg
    Lex, Monika | IuD Bahn | 2007
    Schlagwörter: Betriebliches Lernen

    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

    Decision-making for Connected and Automated Vehicles in Chanllenging Traffic Conditions Using Imitation and Deep Reinforcement Learning

    Hu, Jinchao / Li, Xu / Hu, Weiming et al. | Springer Verlag | 2023
    Schlagwörter: Imitation learning , Deep reinforcement learning

    A robust machine learning structure for driving events recognition using smartphone motion sensors

    Zarei Yazd, Mahdi / Taheri Sarteshnizi, Iman / Samimi, Amir et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: machine learning

    Machine learning techniques to predict reactionary delays and other associated key performance indicators on British railway network

    Taleongpong, Panukorn / Hu, Simon / Jiang, Zhoutong et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    Learning Drivers’ Behavior to Improve Adaptive Cruise Control

    Rosenfeld, Avi / Bareket, Zevi / Goldman, Claudia V. et al. | Taylor & Francis Verlag | 2015
    Schlagwörter: Machine Learning

    Kennzahlen per Intranet

    Becker, Egbert | IuD Bahn | 2004
    Schlagwörter: Betriebliches Lernen

    Efficient Exploitation of Existing Corporate Knowledge in Conceptual Ship Design

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

    Reinforcement learning-enabled genetic algorithm for school bus scheduling

    Köksal Ahmed, Eda / Li, Zengxiang / Veeravalli, Bharadwaj et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: reinforcement learning

    Characterizing aircraft wake vortex position and strength using LiDAR measurements processed with artificial neural networks

    Freier Zugriff
    Wartha, Niklas Louis / Stephan, Anton / Holzäpfel, Frank et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2022
    Schlagwörter: Machine Learning

    An automatic methodology to measure drivers’ behavior in public transport

    Catalán, Hernán / Lobel, Hans / Herrera, Juan Carlos | Taylor & Francis Verlag | 2024
    Schlagwörter: machine learning

    Using kinematic driving data to detect sleep apnea treatment adherence

    McDonald, Anthony D. / Lee, John D. / Aksan, Nazan S. et al. | Taylor & Francis Verlag | 2017
    Schlagwörter: machine learning

    Asynchronous n-step Q-learning adaptive traffic signal control

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

    SHapley Additive exPlanations for Explaining Artificial Neural Network Based Mode Choice Models

    Koushik, Anil / Manoj, M. / Nezamuddin, N. | Springer Verlag | 2024
    Schlagwörter: Deep learning , Machine learning

    Pedestrian Collision Avoidance Using Deep Reinforcement Learning

    Rafiei, Alireza / Fasakhodi, Amirhossein Oliaei / Hajati, Farshid | Springer Verlag | 2022
    Schlagwörter: Deep reinforcement learning , Car Learning to Act (CARLA)

    Estimating the effect of biofouling on ship shaft power based on sensor measurements

    Freier Zugriff
    Bakka, Haakon / Rognebakke, Hanne / Glad, Ingrid et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: machine learning

    Traffic Safety at German Roundabouts—A Replication Study

    Freier Zugriff
    Leich, Andreas / Fuchs, Julian / Srinivas, Gurucharan et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2022
    Schlagwörter: machine learning

    Kreative Seminarmethoden

    Wie Sie den Methodeneinsatz im Training zielgerichtet, effektiv und teilnehmeraktivierend gestalten
    Sander, Silke / Lex, Monika | IuD Bahn | 2005
    Schlagwörter: Betriebliches Lernen

    Projektausbildung in der Berufsausbildung

    Gewinnt immer mehr an Bedeutung
    Krause, Andrea | IuD Bahn | 2004
    Schlagwörter: Betriebliches Lernen

    Trajectory Planning for Automated Parking Systems Using Deep Reinforcement Learning

    Du, Zhuo / Miao, Qiheng / Zong, Changfu | Springer Verlag | 2020
    Schlagwörter: Deep reinforcement learning

    Impact of Training Set Size on the Ability of Deep Neural Networks to Deal with Omission Noise

    Freier Zugriff
    Gütter, Jonas Aaron / Kruspe, Anna / Zhu, Xiao Xiang et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2022
    Schlagwörter: deep learning

    Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

    Aziz, H. M. Abdul / Zhu, Feng / Ukkusuri, Satish V. | Taylor & Francis Verlag | 2018
    Schlagwörter: reinforcement learning

    Estimating cycle-level real-time traffic movements at signalized intersections

    Mahmoud, Nada / Abdel-Aty, Mohamed / Cai, Qing et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    Chancen für die Zukunft durch Bildung

    Berufsbegleitende Fortbildung
    Hebding, Marion | IuD Bahn | 2005
    Schlagwörter: Betriebliches Lernen

    Experimental Closed-Loop Excitation of Nonlinear Normal Modes on an Elastic Industrial Robot

    Freier Zugriff
    Bjelonic, Filip / Sachtler, Arne / Della Santina, Cosimo et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2022
    Schlagwörter: and Learning for Soft Robots

    Systematische Wissensvermittlung mit neuen Medien in der Fortbildung

    E-Learning bei der Bahn
    Pointner, Martin | IuD Bahn | 2005
    Schlagwörter: Betriebliches Lernen

    Arterial corridor travel time prediction under non-recurring conditions

    Shafiei, Sajjad / Wang, Eileen / Grzybowska, Hanna et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: machine learning

    Unobtrusive, natural support control of an adaptive industrial exoskeleton using force myography

    Freier Zugriff
    Sierotowicz, Marek / Brusamento, Donato / Schirrmeister, Benjamin et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2022
    Schlagwörter: machine 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

    Driving cycle recognition neural network algorithm based on the sliding time window for hybrid electric vehicles

    Wang, J. / Wang, Q. N. / Zeng, X. H. et al. | Springer Verlag | 2015
    Schlagwörter: Learning vector quantization

    Application of iterative learning control in tracking a Dubin’s path in parallel parking

    Panomruttanarug, Benjamas | Springer Verlag | 2017
    Schlagwörter: Iterative learning control

    Neural-network-based modelling and analysis for time series prediction of ship motion

    Li, Guoyuan / Kawan, Bikram / Wang, Hao et al. | Taylor & Francis Verlag | 2017
    Schlagwörter: learning strategy

    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

    Deep Architecture for Citywide Travel Time Estimation Incorporating Contextual Information

    Tang, Kun / Chen, Shuyan / Khattak, Aemal J. et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning