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基于ASAMC算法的地质层中氧元素含量的变点问题

A Change-Point Problem of Oxygen Element in Geological Strata Is Based on ASAMC Algorithm
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摘要 变点是地质学的热门问题,多用于微量元素检测,具有很强的应用价值。由Kim,J. and Cheon,S.在2010年提出的退化后的随机逼近蒙特卡罗算法(Annealing Stochastic Approximation Monte Carlo,简称ASAMC);ASAMC算法既可以检测变点个数,又可以检测变点所在的位置。本篇文章基于ASAMC算法,首先对地质层中氧元素含量进行正态性检验,随后,研究不同温度、不同季节下,土壤中氧元素含量的变化情况。最后,利用R软件,我们发现高温多雨的天气会较明显的影响土壤中氧元素的含量。 The change-point is a hot issue in geology, and it is widely used in tracing element detection, and it has strong application value. The annealing stochastic approximation Monte Carlo (ASAMC) algo-rithm proposed by Kim, J. and Cheon, S. in 2010 can detect both the number of change points and the location of change points. In this paper, based on the ASAMC algorithm, the normality test of oxygen content in the geological layer is carried out firstly. Then, the change of oxygen content in the soil under different temperatures and seasons is studied. Last, using R software, we find that the high temperature and rainy weather will obviously affect the oxygen content in the soil.
作者 张梦琇
出处 《应用数学进展》 2022年第9期6161-6170,共10页 Advances in Applied Mathematics
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