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...

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Main Authors: GAO Bin, CAO KeQiang, HU LiangMou, LI ShuGuang
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2018-01-01
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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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