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A correlational research of regional crude oil pipe networks' spatial dimension and regional crude oil production-consumption in China

机译:区域原油管网空间维度与中国区域原油生产消费的关联研究

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Based on regional crude oil pipe networks in China, this paper calculates fractal dimensions of weighted length-radius with the help of the software of Arc GIS. Then this paper analyzes the correlation between crude oil pipe networks' fractal features and crude oil production-consumption upon Z-score data normalization and Pearson's correlation coefficient with the help of the software of SPSS. In sum, the amended results revealed: (1) There is an obvious differentiation of the networks between east and west China in terms of density from the fractal dimensions of weighted length-radius. Meanwhile, the density of networks of northeast, north and east China are relatively higher than northwest and south China. (2) It is primary of crude oil consumption to promote the process of crude oil pipe networks' construction and the Pearson's correlation coefficient between networks fractal features and crude oil consumption is 0.878 (high correlation). On the contrary, the correlation between networks fractal features and crude oil production is so low that the Pearson's correlation coefficient between them only reaches 0.076 (non-correlation). (3) For all the regions, there is such a condition of “high networks density, high crude oil consumption” between east China's networks fractal features and her crude oil consumption. However, here is another condition of “low networks density, low crude oil consumption” between northwest and south China's networks fractal features and her crude oil consumption.
机译:基于中国的区域原油管网,本文在弧GIS软件的帮助下计算加权长度半径的分形维度。然后,本文分析了Z-Score数据标准化和SPSS软件的z评分数据标准化和Pearson相关系数之间的原油管网分形特征与原油生产的相关性。总而言之,修改后的结果显示:(1)在来自加权长度半径的分形尺寸的密度方面,在东部和华西之间的网络存在明显区别。与此同时,东北,北和华东网络的密度比西北和华南相对较高。 (2)原油消耗促进原油管网的建设过程,网络分形特征与原油消耗之间的Pearson的相关系数为0.878(高相关)。相反,网络分形特征与原油生产之间的相关性如此之低,即Pearson之间的相关系数仅达到0.076(非相关)。 (3)对于所有地区,华东网络之间的“高网络密度,高原油消耗”条件和原油消耗等。然而,这是西北和华南网络之间的“低网络密度,低原油消耗”的另一种条件,以及她的原油消费。

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