[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117322-en":3,"doc-seo-117322-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},117322,8796095461610,"Oliver","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Machine Learning for Cyber-Physical Systems - Selected papers from the International Conference ML4CPS 2023","The book compiles selected papers from the International Conference ML4CPS 2023, focusing on machine learning methods for cyber-physical systems. It addresses the challenges that arise when applying ML to CPPS, where data availability is often limited and algorithm behavior can be hard to interpret. Particular attention is given to reliability and testability as crucial properties, reflecting discussions between experts from industry and research on state of the art and new developments. It provides an applied, research-oriented view of how AI can be engineered for real-world cyber-physical use cases.","Technologien für die intelligente Automation Technologies for Intelligent Automation  \nOliver Niggemann Jürgen Beyerer Maria Krantz  \nChristian Kühnert Editors  \nMachine Learning for Cyber-Physical Systems  \nSelected papers from the International Conference ML4CPS 2023  \nTechnologien für die intelligente Automation  \nTechnologies for Intelligent Automation Volume 18  \nReihe herausgegeben von  \nInstitut für industrielle Informationstechnik – inIT, Technische Hochschule  \nOstwestfalen-Lippe, Institut für industrielle Informationstechnik – inIT, Lemgo, Germany  \nZiel der Buchreihe ist die Publikation neuer Ansätze in der Automation auf wissenschaftlichem Niveau, Themen, die heute und in Zukunft entscheidend sind, für die deutsche und internationale Industrie und Forschung. Initiativen wie Industrie 4.0, Industrial Internet oder Cyber-physical Systems machen dies deutlich. Die Anwendbarkeit und der industrielle Nutzen als durchgehendes Leitmotiv der Veröffentlichungen stehen dabei im Vordergrund. Durch diese Verankerung in der Praxis wird sowohl die Verständlichkeitals auch die Relevanz der Beiträge für die Industrie und für die angewandte Forschung gesichert. Diese Buchreihe möchte Lesern eine Orientierung für die neuen Technologien und deren Anwendungen geben und so zur erfolgreichen Umsetzung der Initiativen beitragen.  \nOliver Niggemann · Jürgen Beyerer · Maria Krantz · Christian Kühnert Editors  \nMachine Learning for Cyber-Physical Systems Selected papers from the International Conference ML4CPS 2023  \nEditors  \nOliver Niggemann Fakultät für Maschinenbau Helmut Schmidt University Hamburg, Germany  \nMaria Krantz  \nFakultät für Maschinenbau Helmut Schmidt University Hamburg, Germany  \nJürgen Beyerer Fraunhofer IOSB Karlsruhe, Germany  \nChristian Kühnert Fraunhofer IOSB Karlsruhe, Germany  \nISSN 2522-8579 ISSN 2522-8587 (electronic)  \nTechnologien für die intelligente Automation  \nISBN 978-3-031-47061-5 ISBN 978-3-031-47062-2 (eBook)  \n[https://doi.org/10.1007/978-3-031-47062-2](https://doi.org/10.1007/978-3-031-47062-2)  \n© The Editor(s) (if applicable) and The Author(s) 2024. This book is an open access publication.  \nOpen Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License ([http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/)), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.  \nThe images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.  \nThe 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.  \nThe 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.  \nThis Springer imprint is published by the registered company Springer Nature Switzerland AG  \nThe registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.  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