Time Series Analysis Methods and Applications for Flight Data (Hardcover, 1st ed. 2017)

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Release date

2017

Availability

Expected to ship within 12 - 17 working days

First published

2017

Authors

,

Dimensions

235 x 155 x 21mm (L x W x T)

Format

Hardcover

Pages

240

Edition

1st ed. 2017

ISBN-13

978-3-662-53428-1

Barcode

9783662534281

Categories

LSN

3-662-53428-2



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