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COKRIGING OPTIMIZATION OF MONITORING NETWORK CONFIGURATION BASED ON FUZZY AND NON-FUZZY VARIOGRAM EVALUATION

机译:基于模糊和非模糊变异度评估的监控网络配置协同克里格优化

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摘要

A number of optimization approaches regarding monitoring network design and sampling optimization procedures have been reported in the literature. Cokriging Estimation Variance (CEV) is a useful optimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. It was used in order to derive a reduced configuration of a nitrate concentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering the variogram parameters as fuzzy numbers and the uncertainties by means of membership functions. Fuzzy and non-fuzzy approaches were used to evaluate differences among well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found to require considerably more computational time and numbers of wells at comparable level of information loss.
机译:文献中已经报道了许多有关监视网络设计和采样优化过程的优化方法。 Cokriging估计方差(CEV)是一个有用的优化工具,可以确定监视网络的空间配置对参数估计的影响。使用它是为了导出硝酸盐浓度监测井网络的简化配置。减少的监视配置的可靠性受到定速器选择和一些固有假设的不确定性的影响。这些不确定性可以通过将隶属函数参数作为模糊数来描述,并且可以通过隶属函数来描述。模糊和非模糊方法用于评估井网配置之间的差异。两种方法都可以估算意大利北部摩德纳平原含水层监测网络中硝酸盐浓度可接受的信息损失水平。在信息损失相当的情况下,发现模糊方法需要相当多的计算时间和井数。

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