Predictive modeling of soluble sulfate ion concentration in the Las Vegas Valley

机译：拉斯维加斯山谷中可溶性硫酸根离子浓度的预测模型

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This study investigates the process of identifying soluble sulfate ion concentrations in the Las Vegas Valley. This study was undertaken in an effort to identify factors that may correlate with soluble sulfate ion concentrations and to determine the feasibility of producing a predictive model capable of estimating soluble sulfate ion concentrations within the Las Vegas Valley. The study showed that relief, spatial location, soil grain size classification and Clark County Soils Guideline Map Areas may all provide useful correlations in predicting soluble sulfate ion concentrations. The study produced a preliminary geospatial statistical model capable of identifying large scale trends in the distribution of soluble sulfate ion concentrations. This preliminary model will likely be optimized in the future and serve as the basis for a more accurate and robust predictive model. This study represents the first steps in an effort to better understand the nature of soluble sulfate ion distribution.

机译：这项研究调查了确定拉斯维加斯谷中可溶性硫酸根离子浓度的过程。进行这项研究的目的是确定可能与可溶性硫酸根离子浓度相关的因素，并确定产生能够估算拉斯维加斯山谷中可溶性硫酸根离子浓度的预测模型的可行性。研究表明，地形，空间位置，土壤粒度分类和克拉克县土壤指南图区域都可能在预测可溶性硫酸盐离子浓度方面提供有用的相关性。该研究产生了一个初步的地理空间统计模型，该模型能够确定可溶性硫酸盐离子浓度分布的大规模趋势。该初步模型可能会在将来进行优化，并作为更准确，更可靠的预测模型的基础。这项研究是努力更好地了解可溶性硫酸根离子分布性质的第一步。

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来源
《International Structural Engineering and Construction Conference(ISEC-03); 20050920-23; Shunan(JP)》|2005年|P.279-286|共8页
会议地点 Shunan(JP)
作者
M. Karakouzian; N. Ghafoori; W.K. Hellmer;
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作者单位

University of Nevada, Las Vegas, NV United States;

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原文格式 PDF
正文语种 eng
中图分类混凝土结构、钢筋混凝土结构;
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Predictive modeling of soluble sulfate ion concentration in the Las Vegas Valley

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