کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
506993 865085 2016 8 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
spMC: an R-package for 3D lithological reconstructions based on spatial Markov chains
ترجمه فارسی عنوان
SPMC: یک بسته R برای بازسازی های لیتولوژی 3D بر اساس زنجیره مارکوف فضایی
کلمات کلیدی
اطلاعات طبقه ای؛ احتمالات دگرگونی؛ مدل سازی Transiogram؛ شاخص Cokriging؛ آنتروپی بیزی؛ شبیه سازی/پیش بینی مشروط لیتولوژی 3D
Categorical data; Transition probabilities; Transiogram modeling; Indicator Cokriging; Bayesian entropy; 3D lithological conditional simulation/prediction
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• The open-source R-package “spMC” is presented to deal with spatial Markov Chains.
• The main features are described for graphical analyses, inference and simulations.
• A case study shows the computational capabilities of the implemented functions.

The paper presents the spatial Markov Chains (spMC) R-package and a case study of subsoil simulation/prediction located in a plain site of Northeastern Italy. spMC is a quite complete collection of advanced methods for data inspection, besides spMC implements Markov Chain models to estimate experimental transition probabilities of categorical lithological data. Furthermore, simulation methods based on most known prediction methods (as indicator Kriging and CoKriging) were implemented in spMC package. Moreover, other more advanced methods are available for simulations, e.g. path methods and Bayesian procedures, that exploit the maximum entropy. Since the spMC package was developed for intensive geostatistical computations, part of the code is implemented for parallel computations via the OpenMP constructs. A final analysis of this computational efficiency compares the simulation/prediction algorithms by using different numbers of CPU cores, and considering the example data set of the case study included in the package.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 94, September 2016, Pages 40–47
نویسندگان
, , ,