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Hydraulic Head Interpolation in an Aquifer Unit Using ANFIS and Ordinary Kriging

机译:使用ANFIS和普通Kriging的含水层单元中的液压头插值

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In this study, Ordinary Kriging (OK), and Adaptive Neuro Fuzzy based Inference System (anfis) are evaluated for assessing hydraulic head distribution in an aquifer unit covering 40 km~2. Cartesian coordinates of the samples were used as inputs of anfis. Calibrated models are used to interpolate the hydraulic head distribution on a 50 m square - grid. Both simulations have realistic pattern (R2 > 0.97) even if OK performs slightly better than ANFIS at sampling location. The two methods capture different patterns. The Comparison of the two distributions allow for identifying area of estimate uncertainty, what can be used to improve the sampling network.
机译:在该研究中,普通的Kriging(OK)和自适应神经模糊基于基于基于自适应的神经模糊的推理系统(ANFIS)被评估用于评估覆盖40 km〜2的含水层单元中的液压头分布。样品的笛卡尔坐标被用作ANFI的输入。校准模型用于在50米平方英网上插值液压头分布。这两种模拟都具有现实的模式(R2> 0.97)即使确定在采样位置的ANFIS略微好。这两种方法捕获不同的模式。两个分布的比较允许识别估计不确定性的区域,可用于改进采样网络的内容。

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