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High-Order Sequential Simulation via Statistical Learning in Reproducing Kernel Hilbert Space
The present work proposes a new high-order simulation framework based on statistical learning. The training data consist of the sample data together with a training image, and the learning target is the underlying random field model of spatial attributes of interest. The learning process attempts to...
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| 出版年: | Math Geosci |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer Berlin Heidelberg
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7346981/ https://ncbi.nlm.nih.gov/pubmed/32670433 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11004-019-09843-3 |
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