Short-Term Demand Forecasting of Shared Bicycles Based on Long Short-Term Memory Neural Network Model
Shared bicycles have strong liquidity and high randomness. In order to more accurately predict the short term demand for shared bicycles, the long short-term memory (LSTM) neural network model was used as the tool to predict, on the basis of crawling the
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Xingming Sun Jinwei Wang Elisa Bertino (Eds.)
Artificial Intelligence and Security 6th International Conference, ICAIS 2020 Hohhot, China, July 17–20, 2020 Proceedings, Part I
Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA
Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA
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More information about this series at http://www.springer.com/series/7409
Xingming Sun Jinwei Wang Elisa Bertino (Eds.) •
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Artificial Intelligence and Security 6th International Conference, ICAIS 2020 Hohhot, China, July 17–20, 2020 Proceedings, Part I
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Editors Xingming Sun Nanjing University of Information Science Nanjing, China
Jinwei Wang Nanjing University of Information Science Nanjing, China
Elisa Bertino Purdue University West Lafayette, IN, USA
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-57883-1 ISBN 978-3-030-57884-8 (eBook) https://doi.org/10.1007/978-3-030-57884-8 LNCS Sublibrary: SL3 – Information Systems and Applications, incl. Internet/Web, and HCI © 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 to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
The 6th International Conference on Artificial Intelligence and Security (ICAIS 2020), formerly called the International Conference on Cloud Computing and Security (ICCCS), was held during July 17–20, 2020, in Hohhot, China. Over the past five years, ICAIS has
