کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4575189 1629531 2009 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Spatial prediction of soil properties in temperate mountain regions using support vector regression
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Spatial prediction of soil properties in temperate mountain regions using support vector regression
چکیده انگلیسی

Digital soil mapping in mountain areas faces two major limitations: the small number of available observations and the non-linearity of the relations between environmental variables and soil properties.A possible approach to deal with these limitations involves the use of non-parametric models to interpolate soil properties of interest. Among the different approaches currently available, Support Vector Regression (SVR) seems to have several advantages over other techniques. SVR is a set of techniques in which model complexity is limited by the learning algorithm itself, which prevents overfitting. Moreover, the non-linear approximation of SVR is based on a kernel transformation of the data, which avoids the use of complex functions and is computationally feasible; while the resulting projection in feature space is especially suited for sparse datasets.A brief introduction to this methodology, a comparison with other popular methodologies and a framework for the application of this approach to a study site in the Italian Alps is discussed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Geoderma - Volume 151, Issues 3–4, 15 July 2009, Pages 338–350
نویسندگان
,