ISBN: 9783658363352 - unsupervised pattern discovery in automotive time series: pattern-based construction of representative driving cycles: 159 (12 risultati)

Condizione: New. In English.

Condizione: New.

Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

Taschenbuch. 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.…

Condizione: New.

Condizione: new. Questo è un articolo print on demand.

PF. Condizione: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Taschenbuch. 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. …

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fabian Kai Dietrich&nbspNoering 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. …

Condizione: New. Print on Demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.…

Condizione: New. PRINT ON DEMAND.