Time Series Analysis Methods and Applications for Flight Data

✍ Scribed by Jianye Zhang, Peng Zhang (auth.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2017
• Tongue: English
• Leaves: 244
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-x
Introduction....Pages 1-17
Preprocessing of Flight Data....Pages 19-63
Typical Time Series Analysis of Flight Data Based on ARMA Model....Pages 65-85
Similarity Search for Flight Data....Pages 87-151
Condition Monitoring and Trend Prediction Based on Flight Data....Pages 153-213
Design and Implementation of Flight Data Mining System....Pages 215-231
Back Matter....Pages 233-240

✦ Subjects

Aerospace Technology and Astronautics;Computational Intelligence;Data Mining and Knowledge Discovery;Artificial Intelligence (incl. Robotics)