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Study on the SVM processing model of the GPS monitoring data of coal mine subsidence

Authors
Zhang, Jun
Issue Date
Jun-2014
Publisher
Scitec Publications Ltd.
Keywords
Coal mine subsidence; GPS monitoring data; SVM; processing model
Citation
Applied Mechanics and Materials, v.598, pp 436 - 441
Pages
6
Indexed
SCIE
SCOPUS
Journal Title
Applied Mechanics and Materials
Volume
598
Start Page
436
End Page
441
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116140
DOI
10.4028/www.scientific.net/AMM.598.436
ISSN
1660-9336
Abstract
In order to make the GPS monitoring data of coal mine subsidence useful and effective in engineering practice, this paper tries to analyze the exceptional handling processing model of the GPS monitoring data of coal mine subsidence under the guidance of the principle of support vector machine (SVM) regression, its calculating method and the application of regression program produced by MATLAB. By comparing the result of the exceptional handling processing model established on practical measured data with the one of the polynomial function fitting, this thesis proves that the application of vector regression algorithm in studies on the exceptional handling processing model of the GPS monitoring data is highly effective.
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COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

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ZHANG, Jun
ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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