3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM
Aiming at the fact that the 3-parameter Weibull distribution model is complex and traditional methods have a low accuracy rate in the case of small samples,a new parameter estimation method based on GM-SVM was proposed. Grey model( GM) and support vector machine( SVM) were combined in this method. F...
Main Authors: | , , , |
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Format: | Article |
Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2018-01-01
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Series: | Jixie qiangdu |
Subjects: | |
Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.03.021 |
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author | GAO Bin CAO KeQiang HU LiangMou LI ShuGuang |
author_facet | GAO Bin CAO KeQiang HU LiangMou LI ShuGuang |
author_sort | GAO Bin |
collection | DOAJ |
description | Aiming at the fact that the 3-parameter Weibull distribution model is complex and traditional methods have a low accuracy rate in the case of small samples,a new parameter estimation method based on GM-SVM was proposed. Grey model( GM) and support vector machine( SVM) were combined in this method. Firstly,to take advantages of location parameter estimation based on GM method. Secondly,making full use of the accurate estimated results based on SVM in small samples.This method is applied to the establishment of a Weibull distribution parameter estimation model based on GM and SVM,and to the reliability life distribution parameter estimation of certain engine blade. The simulation test results show that this model has preferable parameter estimation accuracy,has obvious advantages in small samples. This model can accurately obtain the three parameters of Weibull distribution. |
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format | Article |
id | doaj.art-936b99c00f124db1b5428d6c07d9256f |
institution | Directory Open Access Journal |
issn | 1001-9669 |
language | zho |
last_indexed | 2024-03-12T20:44:17Z |
publishDate | 2018-01-01 |
publisher | Editorial Office of Journal of Mechanical Strength |
record_format | Article |
series | Jixie qiangdu |
spelling | doaj.art-936b99c00f124db1b5428d6c07d9256f2023-08-01T07:47:02ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692018-01-0140632638306018463-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVMGAO BinCAO KeQiangHU LiangMouLI ShuGuangAiming at the fact that the 3-parameter Weibull distribution model is complex and traditional methods have a low accuracy rate in the case of small samples,a new parameter estimation method based on GM-SVM was proposed. Grey model( GM) and support vector machine( SVM) were combined in this method. Firstly,to take advantages of location parameter estimation based on GM method. Secondly,making full use of the accurate estimated results based on SVM in small samples.This method is applied to the establishment of a Weibull distribution parameter estimation model based on GM and SVM,and to the reliability life distribution parameter estimation of certain engine blade. The simulation test results show that this model has preferable parameter estimation accuracy,has obvious advantages in small samples. This model can accurately obtain the three parameters of Weibull distribution.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.03.0213-Parameter Weibull distribution;Small samples;Grey model;Support vector machine |
spellingShingle | GAO Bin CAO KeQiang HU LiangMou LI ShuGuang 3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM Jixie qiangdu 3-Parameter Weibull distribution;Small samples;Grey model;Support vector machine |
title | 3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM |
title_full | 3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM |
title_fullStr | 3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM |
title_full_unstemmed | 3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM |
title_short | 3-PARAMETER WEIBULL DISTRIBUTION ESTIMATION BASED ON GM AND SVM |
title_sort | 3 parameter weibull distribution estimation based on gm and svm |
topic | 3-Parameter Weibull distribution;Small samples;Grey model;Support vector machine |
url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.03.021 |
work_keys_str_mv | AT gaobin 3parameterweibulldistributionestimationbasedongmandsvm AT caokeqiang 3parameterweibulldistributionestimationbasedongmandsvm AT huliangmou 3parameterweibulldistributionestimationbasedongmandsvm AT lishuguang 3parameterweibulldistributionestimationbasedongmandsvm |