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Time series analysis methods and applications for flight data / Jianye Zhang, Peng Zhang.

By: Zhang, Jianye.
Contributor(s): Zhang, Peng.
Material type: materialTypeLabelE-bookPublisher: Berlin, Germany : Springer, 2017Description: 1 recurso en línea.ISBN: 3662534304; 9783662534304.Subject: Data miningOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
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.
Abstract: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA280 .Z436 2017 EB (Browse shelf(Opens below)) Acceso electrónico eBook.20022688
Total holds: 0

SpringerLink Springer Engineering eBooks 2017 English+International

Incluye referencias bibliográficas

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.

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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