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Titlebook: Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Enviro; Challenges, Processe N. Janardhana Ra

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發(fā)表于 2025-3-23 12:04:15 | 只看該作者
Captured Content: Captured Attention?multi-dimensional probability-based statistical technique, which is superior to the use of conventional bi-variate or ternary diagrams. Application of this procedure is illustrated with three subsets of compositional data for 2270 igneous rock samples from the central part of the Mexican Volcanic Be
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發(fā)表于 2025-3-23 14:28:34 | 只看該作者
13#
發(fā)表于 2025-3-23 20:30:12 | 只看該作者
What Is the Nature of Accommodations?, network under spatially or temporally varying flow velocities and dispersion coefficients. This method employs the generalized integral transform technique (GITT) and general linear transformation method by Clement [2001] to transform the set of coupled multispecies reactive transport equations int
14#
發(fā)表于 2025-3-23 23:32:04 | 只看該作者
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發(fā)表于 2025-3-24 04:02:48 | 只看該作者
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發(fā)表于 2025-3-24 09:47:30 | 只看該作者
Sofie Bager-Charleson,Alistair McBeathr as data object the entire PSC with a Compositional Data Analysis (CoDa) approach. Data are viewed as a point in the infinite-dimensional Hilbert space of functional compositions. The latter is endowed with the Aitchison geometry and enables us to derive a Functional Compositional Kriging (FCK) pre
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發(fā)表于 2025-3-24 11:56:53 | 只看該作者
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發(fā)表于 2025-3-24 18:29:52 | 只看該作者
19#
發(fā)表于 2025-3-24 20:18:48 | 只看該作者
https://doi.org/10.1057/9781137315571re that the variable of interest average linearly. By quantifying and modeling the metallurgical properties of blends, these metallurgical variables can be spatially modeled and scaled. Atheoretical framework for the re-expression of these nonlinear metallurgical variables to linear variables using
20#
發(fā)表于 2025-3-24 23:55:33 | 只看該作者
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