Quantifying Geological Uncertainty Using Conditioned Spatial Markov Chains-Reference-Cited by-同舟云学术

Quantifying Geological Uncertainty Using Conditioned Spatial Markov Chains

Published:2022-03-17 Issue: Volume: Page:
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Container-title:Geo-Congress 2022
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Author:

Oluwatuyi Opeyemi E.¹²³⁴,Rajapakshage Rasika¹²³⁴,Wulff Shaun S.¹²³⁴,Ng Kam¹²³⁴

Affiliation:

1. Ph.D. Student, Dept. of Civil and Architectural Engineering, Univ. of Wyoming, Laramie, WY.

2. Postdoctoral, Dept. of Mathematics and Statistics, Univ. of Wyoming, Laramie, WY.

3. Professor, Dept. of Mathematics and Statistics, Univ. of Wyoming, Laramie, WY.

4. Associate Professor, Dept. of Civil and Architectural Engineering, Univ. of Wyoming, Laramie, WY.

Publisher

American Society of Civil Engineers

Link

http://ascelibrary.org/doi/pdf/10.1061/9780784484036.043

Reference9 articles.

1. Reducing geological uncertainty by conditioning on boreholes: the coupled Markov chain approach

2. Quantifying stratigraphic uncertainties by stochastic simulation techniques based on Markov random field

3. Role of reliability calculations in geotechnical design

4. R Core Team. (2016). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria. (https://www.R-project.org).

5. SpMC: Modelling spatial random fields with continuous Lag Markov Chains;Sartore L.;R Journal,2013

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