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OverviewThis open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction. Full Product DetailsAuthor: Oliver Niggemann , Peter SchüllerPublisher: Springer Fachmedien Wiesbaden Imprint: Springer Vieweg Edition: 1st ed. 2018 Volume: 8 Weight: 0.454kg ISBN: 9783662578049ISBN 10: 3662578042 Pages: 129 Publication Date: 31 August 2018 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationProf. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo. Dr. Peter Schüller is postdoctoral researcher at Technische Universität Wien. His research interests are hybrid reasoning systems that combine Knowledge Representation and Machine Learning and applications in the fields of Cyber-Physical systems and Natural Language Processing. Tab Content 6Author Website:Countries AvailableAll regions |
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