Artificial Neural Networks for the Estimation of Pedestrian Interaction Forces
We present a data fitting approach for the social force model by Helbing and Molnár using artificial neural networks. The latter are used as a universal approximation for the unknown interaction forces between pedestrians. We train the artificial neural n
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Livio Gibelli Editor
Crowd Dynamics, Volume 2 Theory, Models, and Applications
Modeling and Simulation in Science, Engineering and Technology Series Editors Nicola Bellomo Department of Mathematical Sciences Politecnico di Torino Torino, Italy
Tayfun E. Tezduyar Department of Mechanical Engineering Rice University Houston, TX, USA
Editorial Board Members Kazuo Aoki National Taiwan University Taipei, Taiwan Yuri Bazilevs School of Engineering Brown University Providence, RI, USA Mark Chaplain School of Mathematics and Statistics University of St. Andrews St. Andrews, UK Pierre Degond Department of Mathematics Imperial College London London, UK Andreas Deutsch Center for Information Services and High-Performance Computing Technische Universität Dresden Dresden, Sachsen, Germany Livio Gibelli Institute for Multiscale Thermofluids University of Edinburgh Edinburgh, UK Miguel Ángel Herrero Departamento de Matemática Aplicada Universidad Complutense de Madrid Madrid, Spain
Petros Koumoutsakos Computational Science and Engineering Laboratory ETH Zürich Zürich, Switzerland Andrea Prosperetti Cullen School of Engineering University of Houston Houston, TX, USA K. R. Rajagopal Department of Mechanical Engineering Texas A&M University College Station, TX, USA Kenji Takizawa Department of Modern Mechanical Engineering Waseda University Tokyo, Japan Youshan Tao Department of Applied Mathematics Donghua University Shanghai, China Harald van Brummelen Department of Mechanical Engineering Eindhoven University of Technology Eindhoven, Noord-Brabant, The Netherlands
Thomas J. R. Hughes Institute for Computational Engineering and Sciences The University of Texas at Austin Austin, TX, USA
More information about this series at http://www.springer.com/series/4960
Livio Gibelli Editor
Crowd Dynamics, Volume 2 Theory, Models, and Applications
Editor Livio Gibelli Institute for Multiscale Thermofluids University of Edinburgh Edinburgh, UK
ISSN 2164-3679 ISSN 2164-3725 (electronic) Modeling and Simulation in Science, Engineering and Technology ISBN 978-3-030-50449-6 ISBN 978-3-030-50450-2 (eBook) https://doi.org/10.1007/978-3-030-50450-2 Mathematics Subject Classification: 34H05, 35Q93, 90B20, 91B99, 93A30 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe t
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