Samui, Pijush and Bhattacharya, Gautam and Choudhury, Deepankar (2009) Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach. In: 12th Online World Conference on Soft Computing in Industrial Applications (WFSC 12), OCT 16-26, 2007, England.
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Abstract
This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.
Item Type: | Conference Paper |
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Publisher: | Springer |
Additional Information: | Copyright of this publications belongs to Springer. |
Keywords: | pile;clay;relevance vector machine;ultimate capacity. |
Department/Centre: | Division of Mechanical Sciences > Civil Engineering |
Date Deposited: | 09 Feb 2010 11:23 |
Last Modified: | 19 Sep 2010 05:31 |
URI: | http://eprints.iisc.ac.in/id/eprint/19986 |
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