Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number

Grey theory is an essential uncertain knowledge acquisition method for small sample, poor information. The classic grey theory does not adequately take into account the distribution of data set and lacks the effective methods to analyze and mine big sample in multigranularity. In view of the univers...

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Main Authors: Jin Dai, Xin Liu, Feng Hu
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/312645
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author Jin Dai
Xin Liu
Feng Hu
author_facet Jin Dai
Xin Liu
Feng Hu
author_sort Jin Dai
collection DOAJ
description Grey theory is an essential uncertain knowledge acquisition method for small sample, poor information. The classic grey theory does not adequately take into account the distribution of data set and lacks the effective methods to analyze and mine big sample in multigranularity. In view of the universality of the normal distribution, the normality grey number is proposed. Then, the corresponding definition and calculation method of the relational degree between the normality grey numbers are constructed. On this basis, the grey relational analytical method in multigranularity is put forward to realize the automatic clustering in the specified granularity without any experience knowledge. Finally, experiments fully prove that it is an effective knowledge acquisition method for big data or multigranularity sample.
format Article
id doaj-art-8291e3dc4bb141f7992f9680f8d662cf
institution OA Journals
issn 2356-6140
1537-744X
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-8291e3dc4bb141f7992f9680f8d662cf2025-08-20T02:08:45ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/312645312645Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey NumberJin Dai0Xin Liu1Feng Hu2College of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Computer Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaGrey theory is an essential uncertain knowledge acquisition method for small sample, poor information. The classic grey theory does not adequately take into account the distribution of data set and lacks the effective methods to analyze and mine big sample in multigranularity. In view of the universality of the normal distribution, the normality grey number is proposed. Then, the corresponding definition and calculation method of the relational degree between the normality grey numbers are constructed. On this basis, the grey relational analytical method in multigranularity is put forward to realize the automatic clustering in the specified granularity without any experience knowledge. Finally, experiments fully prove that it is an effective knowledge acquisition method for big data or multigranularity sample.http://dx.doi.org/10.1155/2014/312645
spellingShingle Jin Dai
Xin Liu
Feng Hu
Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number
The Scientific World Journal
title Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number
title_full Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number
title_fullStr Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number
title_full_unstemmed Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number
title_short Research and Application for Grey Relational Analysis in Multigranularity Based on Normality Grey Number
title_sort research and application for grey relational analysis in multigranularity based on normality grey number
url http://dx.doi.org/10.1155/2014/312645
work_keys_str_mv AT jindai researchandapplicationforgreyrelationalanalysisinmultigranularitybasedonnormalitygreynumber
AT xinliu researchandapplicationforgreyrelationalanalysisinmultigranularitybasedonnormalitygreynumber
AT fenghu researchandapplicationforgreyrelationalanalysisinmultigranularitybasedonnormalitygreynumber