Determination of Compression Index for Marine Clay: A Relevance Vector Machine Approach SCIE SCOPUS

Cited 1 time in WEB OF SCIENCE Cited 1 time in Scopus
Title
Determination of Compression Index for Marine Clay: A Relevance Vector Machine Approach
Author(s)
Samui, Pijush; Kim, Dookie; Das, Sarat; Yoon, Gil Lim
KIOST Author(s)
Yoon, Gil Lim(윤길림)
Publication Year
2012
Abstract
This study investigates the feasibility of Relevance Vector Machine (RVM) for determination of Compression Index (C-c) of marine clay. RVM allows computation of the prediction intervals taking into account uncertainties of both the parameters and the data. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. The input parameters of RVM are natural water content (omega(n)), liquid limit (omega(1)), initial void ratio (e(0)), and dry density (gamma(d)). Equations have also been developed for the prediction of C-c of marine clay. The developer RVM model gives variance of the predicted C-c. A comparative study has also been done between the developed RVM and regression models. The results indicate that RVM is a useful technique for predicting C-c of marine clay.
ISSN
1064-119X
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/3750
DOI
10.1080/1064119X.2011.614323
Bibliographic Citation
MARINE GEORESOURCES & GEOTECHNOLOGY, v.30, no.4, pp.263 - 273, 2012
Publisher
TAYLOR & FRANCIS INC
Keywords
compression index; marine clay; relevance vector machine; variance
Type
Article
Language
English
Document Type
Article
Publisher
TAYLOR & FRANCIS INC
Related Researcher
Research Interests

marine geotechnics,Dredging & Soft Ground,Offshore Wind Foundations,해양지반공학,준설 및 연약지반,해상풍력기초 및 신뢰성설계

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