灰色周期事件模型及其修复

Hongyun Du, Hongxing Shi, Chuanping Song, Yong Zhao
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引用次数: 18

摘要

灰色关联模型从统计序列几何形式的接近度和相似度来确定其接近度。传统的灰色关联模型从面积、坡度、变化速度等角度计算统计序列关联度。这些发病率模型受到水平坐标和垂直坐标的双重影响。随后,当我们分析统计序列与个体因素之间的关系时,就会产生其他因素的推断。为了克服这一局限,作者提出了周期相关模型,并得出该模型参考了波浪的波动周期,但与波浪的摆动无关,并能表现出正负相关的结论。应用该模型对GDP与居民消费的周期关系进行了研究,结果表明该模型是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The model of grey periodic incidence and their rehabilitation
Grey incidence model determines the closeness degree from the closeness and similarity of statistical sequencepsilas geometrical form. Traditional grey incidence model calculates statistical sequencepsilas correlation degree from the perspectives of its acreage, slope, changing velocity, etc. These incidence models have dual influences exerted by horizontal and vertical coordinates. Subsequently, inference of other factors occurs when we analyze the relationship between statistical sequencepsilas individual factors. To overcome this limitation, the author puts forward the periodic correlation model and draws the conclusion that the model is in reference to the fluctuation period of the wave, but is independent of its swing, and that it can show the positive-negative relevance. This model is then applied to carry out a research into the periodical relationship between GDP and residential consumption, which comes out to be an effective one.
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