Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters

Abstract Collapsibility determination in loess area is expensive, and it also requires a large amount of experimentation. This paper aims to find the association rules between physical parameters and collapsibility of the loess in Xining through the method of data mining, so to help researchers pred...

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Autores principales:	Zhikun Li, Xiaojun Li, Yanyan Zhu, Shi Dong, Chenzhi Hu, Jixin Fan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6a0e4fa485db4ddbbb36cd6b2241336c
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spelling	oai:doaj.org-article:6a0e4fa485db4ddbbb36cd6b2241336c2021-12-02T14:01:37ZMining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters10.1038/s41598-020-78702-72045-2322https://doaj.org/article/6a0e4fa485db4ddbbb36cd6b2241336c2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78702-7https://doaj.org/toc/2045-2322Abstract Collapsibility determination in loess area is expensive, and it also requires a large amount of experimentation. This paper aims to find the association rules between physical parameters and collapsibility of the loess in Xining through the method of data mining, so to help researchers predict the collapsibility of loess. Related physical parameters of loess collapsibility, collected from 1039 samples, involve 13 potential influence factors. According to Grey Relational Analysis, the key influence factors that lead to collapsing are identified from these potential influence factors. Subsequently, take the key influence factors, δs (coefficient of collapsibility) and δzs (coefficient of collapsibility under overburden pressure) as input items, and use the Apriori algorithm to find multiple association rules between them. Then, through analysing the results of association rules between these key influence factors and collapsibility, the evaluation criteria for collapsibility in this area is proposed, which can be used to simplify the workload of determining collapsibility. Finally, based on these research results, recommendations for projects construction were made to ensure the safety of construction in the area.Zhikun LiXiaojun LiYanyan ZhuShi DongChenzhi HuJixin FanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zhikun Li Xiaojun Li Yanyan Zhu Shi Dong Chenzhi Hu Jixin Fan Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters
description	Abstract Collapsibility determination in loess area is expensive, and it also requires a large amount of experimentation. This paper aims to find the association rules between physical parameters and collapsibility of the loess in Xining through the method of data mining, so to help researchers predict the collapsibility of loess. Related physical parameters of loess collapsibility, collected from 1039 samples, involve 13 potential influence factors. According to Grey Relational Analysis, the key influence factors that lead to collapsing are identified from these potential influence factors. Subsequently, take the key influence factors, δs (coefficient of collapsibility) and δzs (coefficient of collapsibility under overburden pressure) as input items, and use the Apriori algorithm to find multiple association rules between them. Then, through analysing the results of association rules between these key influence factors and collapsibility, the evaluation criteria for collapsibility in this area is proposed, which can be used to simplify the workload of determining collapsibility. Finally, based on these research results, recommendations for projects construction were made to ensure the safety of construction in the area.
format	article
author	Zhikun Li Xiaojun Li Yanyan Zhu Shi Dong Chenzhi Hu Jixin Fan
author_facet	Zhikun Li Xiaojun Li Yanyan Zhu Shi Dong Chenzhi Hu Jixin Fan
author_sort	Zhikun Li
title	Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters
title_short	Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters
title_full	Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters
title_fullStr	Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters
title_full_unstemmed	Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters
title_sort	mining and analysis of multiple association rules between the xining loess collapsibility and physical parameters
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6a0e4fa485db4ddbbb36cd6b2241336c
work_keys_str_mv	AT zhikunli miningandanalysisofmultipleassociationrulesbetweenthexiningloesscollapsibilityandphysicalparameters AT xiaojunli miningandanalysisofmultipleassociationrulesbetweenthexiningloesscollapsibilityandphysicalparameters AT yanyanzhu miningandanalysisofmultipleassociationrulesbetweenthexiningloesscollapsibilityandphysicalparameters AT shidong miningandanalysisofmultipleassociationrulesbetweenthexiningloesscollapsibilityandphysicalparameters AT chenzhihu miningandanalysisofmultipleassociationrulesbetweenthexiningloesscollapsibilityandphysicalparameters AT jixinfan miningandanalysisofmultipleassociationrulesbetweenthexiningloesscollapsibilityandphysicalparameters
_version_	1718392145087299584

Mining and analysis of multiple association rules between the Xining loess collapsibility and physical parameters

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