Determination of Compression Index For Marine Clay: A Least Square Support Vector Machine Approach
نویسندگان
چکیده
This article employs Least Square Support Vector Machine (LSSVM) for determination of Compression Index (Cc) of marine clay in east coast of Korea. This study uses LSSVM as a regression tool. In LSSVM, the regression equation is obtained as the solution to a linear system instead of a quadratic programming (QP) problem. The input parameters of LSSVM are natural water content (n), liquid limit (1), initial void ratio (e0), and plasticity index (PI). Equations have been also developed for the prediction of Cc of marine clay. The comparison between the developed LSSVM and the regression models shows that the developed LSSVM models perform better than the regression models. This article shows that the developed LSSVM can be used to predict Cc of marine clay in east coast of Korea.
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