Time Series Analysis Methods and Applications for Flight Data

Peng Zhang

ISBN 10: 3662571366 / ISBN 13: 9783662571361

Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2018, 2018

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This item is printed on demand - Print on Demand Titel. Neuware -This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch.

Codice articolo 9783662571361

Dati bibliografici

• Titolo: Time Series Analysis Methods and Applications for Flight Data
• Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2018
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 3662571366
• ISBN 13: 9783662571361
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 14 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 14 millimetri di profondità
• Peso: 388 grammi

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Riassunto

This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.