Time series analysis methods and applications for flight data / Jianye Zhang, Peng Zhang.
Zhang, Jianye.; Zhang, Peng.
2017
QA280
Available Online

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Title Time series analysis methods and applications for flight data / Jianye Zhang, Peng Zhang.
Author Zhang, Jianye.
ISBN 9783662534304 (electronic book)
3662534304 (electronic book)
9783662534281
3662534282
DOI https://doi.org/10.1007/978-3-662-53430-4
Publication Details Berlin, Germany : Springer, 2017.
Language English
Description 1 online resource
Item Number 10.1007/978-3-662-53430-4 doi
Call Number QA280
Dewey Decimal Classification 519.5/5
620
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Description based on print version record.
Added Author Zhang, Peng.
Available in Other Form Print version: 9783662534281
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Introduction
Preprocessing of Flight Data
Typical Time Series Analysis for Flight Data
Similarity Search for Flight Data
Condition Monitoring and Trend Prediction Based on Flight Data
Design and Implementation Of flight Data Mining System.

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