Please use this identifier to cite or link to this item:

TitleUse of data mining in design of soil improvement by jet grouting
Author(s)Correia, A. Gomes
Tinoco, Joaquim Agostinho Barbosa
Cortez, Paulo
KeywordsSoil improvement
Jet grouting
Mechanical properties
Data mining
Support vector machines
Sensitivity analysis
Issue date20-Jul-2014
PublisherIOS Press
Abstract(s)This paper addresses one of the main issues related to Jet Grouting (JG) technology, that is, the design of the mechanical properties of the soil-cement mixture. Thus, one of the most powerful Data Mining (DM) algorithms is applied, that is, Support Vector Machine (SVM), towards to the development of a new and more accurate approach for Uniaxial Compressive Strength (UCS) and stiffness prediction of both Jet Grouting Laboratory Formulations (JGLF) and soilcrete mixtures. The obtained results show that SVM algorithm can be used to accurately predict both strength and stiffness of JGLF. Related to soilcrete mixtures, it is shown that the SVM algorithm, despite some of the difficulties found, can give an important contribution for a better understanding of JG technology. Based on a detailed Sensitivity Analysis (SA) some important observations were made, which certainly will contribute for JG technical and economic efficiency improvement
TypeConference paper
Publisher version
AccessRestricted access (UMinho)
Appears in Collections:ISISE - Comunicações a Conferências Internacionais

Files in This Item:
File Description SizeFormat 
  Restricted access
Full paper613,08 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID