کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4642603 | 1341349 | 2007 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Creating a quality map of a slate deposit using support vector machines Creating a quality map of a slate deposit using support vector machines](/preview/png/4642603.png)
In this work, we create a quality map of a slate deposit, using the results of an investigation based on surface geology and continuous core borehole sampling. Once the quality of the slate and the location of the sampling points have been defined, different kinds of support vector machines (SVMs)—SVM classification (multiclass one-against-all), ordinal SVM and SVM regression—are used to draw up the quality map. The results are also compared with those for kriging.The results obtained demonstrate that SVM regression and ordinal SVM are perfectly comparable to kriging and possess some additional advantages, namely, their interpretability and control of outliers in terms of the support vectors.Likewise, the benefits of using the covariogram as the kernel of the SVM are evaluated, with a view to incorporating the problem association structure in the feature space geometry. In our problem, this strategy not only improved our results but also implied substantial computational savings.
Journal: Journal of Computational and Applied Mathematics - Volume 204, Issue 1, 1 July 2007, Pages 84–94