Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 78,24
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Editore: Springer Fachmedien Wiesbaden, Weisbaden, 2022
ISBN 10: 3658363355 ISBN 13: 9783658363352
Lingua: Inglese
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Prima edizione
Paperback. Condizione: new. Paperback. In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles. In the last decade unsupervised pattern discovery in time series, i.e. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 83,45
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: Brook Bookstore, Milano, MI, Italia
EUR 73,50
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 98,07
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Da: Chiron Media, Wallingford, Regno Unito
EUR 97,93
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Aggiungi al carrelloPF. Condizione: New.
Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Editore: Springer Fachmedien Wiesbaden, Springer Fachmedien Wiesbaden Mär 2022, 2022
ISBN 10: 3658363355 ISBN 13: 9783658363352
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 96,29
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles.Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 172 pp. Englisch.
Editore: Springer Fachmedien Wiesbaden, 2022
ISBN 10: 3658363355 ISBN 13: 9783658363352
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 96,29
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles.
Editore: Springer Fachmedien Wiesbaden, Weisbaden, 2022
ISBN 10: 3658363355 ISBN 13: 9783658363352
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
Prima edizione
EUR 133,19
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles. In the last decade unsupervised pattern discovery in time series, i.e. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: Revaluation Books, Exeter, Regno Unito
EUR 93,25
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Aggiungi al carrelloPaperback. Condizione: Brand New. 169 pages. 8.26x5.82x0.37 inches. In Stock. This item is printed on demand.
Editore: Springer Fachmedien Wiesbaden Mrz 2022, 2022
ISBN 10: 3658363355 ISBN 13: 9783658363352
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 96,29
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles. 172 pp. Englisch.
Editore: Springer Fachmedien Wiesbaden, 2022
ISBN 10: 3658363355 ISBN 13: 9783658363352
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 83,50
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fabian Kai Dietrich Noering is currently working in the technical development of Volkswagen AG as data scientist with a special interest in the analysis of time series regarding e.g. product optimization.In the last decade u.
Da: Majestic Books, Hounslow, Regno Unito
EUR 137,96
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 138,17
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