Time Series Analysis Methods and Applications for Flight Data (Record no. 80417)

000 -LEADER
fixed length control field 03212nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-3-662-53430-4
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801222122.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 161222s2017 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783662534304
-- 978-3-662-53430-4
082 04 - CLASSIFICATION NUMBER
Call Number 629.1
100 1# - AUTHOR NAME
Author Zhang, Jianye.
245 10 - TITLE STATEMENT
Title Time Series Analysis Methods and Applications for Flight Data
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages X, 240 p. 161 illus., 35 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Zhang, Peng.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-662-53430-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2017.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Aerospace engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Astronautics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Aerospace Technology and Astronautics.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
912 ## -
-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE

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