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首页> 外文期刊>Journal of soil & sediments >Applying regularized logistic regression (RLR) for the discrimination of sediment facies in reservoirs based on composite fingerprints
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Applying regularized logistic regression (RLR) for the discrimination of sediment facies in reservoirs based on composite fingerprints

机译:基于复合指纹识别的正则逻辑回归(RLR)在储层泥沙相识别中的应用

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摘要

Soils and sediments can be distinguished based on "composite fingerprints", i.e., sets of physical and chemical properties that are suitable for discrimination. At present, statistical stepwise variable selection methods are frequently applied to identify composite fingerprints, although they have been seriously criticized. Here, we test regularized logistic regression (RLR) as an alternative approach in the context of a reservoir siltation study where the post-dam facies is to be distinguished from the pre-dam facies.
机译:可以基于“复合指纹”,即适于区分的一组物理和化学特性来区分土壤和沉积物。目前,统计逐步变量选择方法经常被用来识别复合指纹,尽管它们已受到严重批评。在这里,我们在水库淤积研究的背景下测试正则逻辑回归(RLR)作为替代方法,在该研究中,要区分大坝后相和大坝前相。

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