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Lognormal Kriging: Bias Adjustment and Kriging Variances
2005Lognormality of spatial data occurs commonly enough for it to warrant continued study; contemporary statistical and computational methodologies can shed new light on the old problem of block kriging for lognormal processes. There are a number of proposals available for block kriging, many of them discussed in an unpublished, 43-page, Centre de ...
Noel Cressie, Martina Pavlicová
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Computer Methods in Applied Mechanics and Engineering, 2019
In this paper, the adaptive importance sampling (AIS) method is extended for hybrid reliability analysis under random and interval variables (HRA-RI) with small failure probabilities.
Jinhao Zhang, Mi Xiao, Liang Gao, S. Chu
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In this paper, the adaptive importance sampling (AIS) method is extended for hybrid reliability analysis under random and interval variables (HRA-RI) with small failure probabilities.
Jinhao Zhang, Mi Xiao, Liang Gao, S. Chu
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Information Sciences, 2020
In this paper, a novel algorithm KTLBO is presented to achieve computationally expensive constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated surrogate models for costly objective and inequality constraints.
Huachao Dong +3 more
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In this paper, a novel algorithm KTLBO is presented to achieve computationally expensive constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated surrogate models for costly objective and inequality constraints.
Huachao Dong +3 more
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Combination of Machine Learning and Kriging for Spatial Estimation of Geological Attributes
Natural Resources Research, 2022Gamze Erdogan Erten +2 more
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An enhanced Kriging surrogate modeling technique for high-dimensional problems
, 2020Surrogate modeling techniques are widely used to simulate the behavior of manufactured and engineering systems. The construction of such surrogate models may become intractable in cases when input spaces have high dimensions, because the large number of ...
Yicheng Zhou, Zhenzhou Lu
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Kriging based reliability and sensitivity analysis – Application to the stability of an earth dam
, 2020This article presents a Kriging-based probabilistic analysis of an earth dam. The dam failure probability with respect to the sliding stability is investigated by considering the influence of various factors: the filter drain length, the full reservoir ...
Xiangfeng Guo, D. Dias
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2019
Chapter 4 discusses kriging; one calls kriging, or simple kriging, of the random function Y in a panel P the best linear estimator Y K of Y by N samples Y α. This optimum is given by starting from the extension variance of Y − Y K, where Y K = λ α
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Chapter 4 discusses kriging; one calls kriging, or simple kriging, of the random function Y in a panel P the best linear estimator Y K of Y by N samples Y α. This optimum is given by starting from the extension variance of Y − Y K, where Y K = λ α
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Fuzzy Sets and Systems, 1989
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