Advances in Gaussian random field generation: a review

被引:0
|
作者
Yang Liu
Jingfa Li
Shuyu Sun
Bo Yu
机构
[1] King Abdullah University of Science and Technology,Computational Transport Phenomena Laboratory, Division of Physical Science and Engineering
[2] Beijing Institute of Petrochemical Technology,School of Mechanical Engineering, Beijing Key Laboratory of Pipeline Critical Technology and Equipment for Deepwater Oil & Gas Development
来源
Computational Geosciences | 2019年 / 23卷
关键词
Random field generation; Gaussian distribution; Numerical methods; Applications of Gaussian random field; Software and packages;
D O I
暂无
中图分类号
学科分类号
摘要
Gaussian (normal) distribution is a basic continuous probability distribution in statistics, it plays a substantial role in scientific and engineering problems that related to stochastic phenomena. This paper aims to review state-of-the-art of Gaussian random field generation methods, their applications in scientific and engineering issues of interest, and open-source software/packages for Gaussian random field generation. To this end, first, we briefly introduce basic mathematical concepts and theories in the Gaussian random field, then seven commonly used Gaussian random field generation methods are systematically presented. The basic idea, mathematical framework of each generation method are introduced in detail and comparisons of these methods are summarized. Then, representative applications of the Gaussian random field in various areas, especially of engineering interest in recent two decades, are reviewed. For readers’ convenience, four representative example codes are provided, and several relevant up-to-date open-source software and packages that freely available from the Internet are introduced.
引用
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页码:1011 / 1047
页数:36
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