Combination of Fuzzy Logic and Kriging Technique Under Uncertainty for Spatial Data Prediction

S. Ibrahim, G. Dhaher
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引用次数: 1

Abstract

. This paper deals with the spatial prediction in Geostatistics. This paper depend on interpellation methods of spatial statistic (ordinary kriging technique) to combination with fuzzy logic under uncertainty for spatial data prediction. This work includes the best linear unbiased estimator prediction by using formals of linear prediction and variance kriging to find prediction by Appling on real spatial data. The data adopted from real spatial data represented the depth of real underground water wells with real location from Mosul city/Iraq. We took (100) real data with locations in study area. We applied empiricism variogram function to get the properties of variogram function. We combination between kriging technique with fuzzy logic (Mamdani Fuzzy Model). To get the best Mathematical model under uncertainty. We getting the results between kriging and fuzzy logic using Matlab language.This study is a continuation of the research conducted in this context Which is very important to highlight.
不确定条件下模糊逻辑和Kriging技术相结合的空间数据预测
。本文讨论地统计学中的空间预测问题。本文将空间统计的质询方法(普通克里格技术)与不确定条件下的模糊逻辑相结合,对空间数据进行预测。利用线性预测和方差克里金的形式对实际空间数据进行预测,得到最佳的线性无偏估计量预测。采用的数据来自真实空间数据,代表了伊拉克摩苏尔市真实位置的真实地下水井深度。我们在研究区域的位置采集了100个真实数据。应用经验变差函数得到了变差函数的性质。我们将克里金技术与模糊逻辑(Mamdani模糊模型)相结合。得到不确定条件下的最佳数学模型。利用Matlab语言对克里格和模糊逻辑进行了对比分析。本研究是在此背景下进行的研究的延续,这一点非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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24 weeks
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