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Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition...

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Detalles Bibliográficos
Autores principales: Jia, Chaolong, Wei, Lili, Wang, Hanning, Yang, Jiulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236969/
https://www.ncbi.nlm.nih.gov/pubmed/25435869
http://dx.doi.org/10.1155/2014/727948
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author Jia, Chaolong
Wei, Lili
Wang, Hanning
Yang, Jiulin
author_facet Jia, Chaolong
Wei, Lili
Wang, Hanning
Yang, Jiulin
author_sort Jia, Chaolong
collection PubMed
description Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.
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spelling pubmed-42369692014-11-30 Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section Jia, Chaolong Wei, Lili Wang, Hanning Yang, Jiulin Comput Intell Neurosci Research Article Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described. Hindawi Publishing Corporation 2014 2014-11-04 /pmc/articles/PMC4236969/ /pubmed/25435869 http://dx.doi.org/10.1155/2014/727948 Text en Copyright © 2014 Chaolong Jia et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Jia, Chaolong
Wei, Lili
Wang, Hanning
Yang, Jiulin
Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
title Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
title_full Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
title_fullStr Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
title_full_unstemmed Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
title_short Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
title_sort study of track irregularity time series calibration and variation pattern at unit section
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236969/
https://www.ncbi.nlm.nih.gov/pubmed/25435869
http://dx.doi.org/10.1155/2014/727948
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