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首页> 外文期刊>Pure and Applied Geophysics >Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies
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Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies

机译：地震前介绍中的多元线性回归与人工神经网络的时间序列分析

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摘要

This paper reports the analysis of soil radon data recorded in the seismic zone-V, located in the northeastern part of India (latitude 23.73N, longitude 92.73E). Continuous measurements of soil-gas emission along Chite fault in Mizoram (India) were carried out with the replacement of solid-state nuclear track detectors at weekly interval. The present study was done for the period from March 2013 to May 2015 using LR-115 Type II detectors, manufactured by Kodak Pathe, France. In order to reduce the influence of meteorological parameters, statistical analysis tools such as multiple linear regression and artificial neural network have been used. Decrease in radon concentration was recorded prior to some earthquakes that occurred during the observation period. Some false anomalies were also recorded which may be attributed to the ongoing crustal deformation which was not major enough to produce an earthquake.
机译：本文报告了在印度东北部（纬度23.73N，经度92.73e）的地震区-V中记录的土壤氡数据分析。 在每周间隔内更换固态核轨道探测器，在Mizoram（印度）中沿着Chite故障进行连续测量。 本研究于2013年3月至2015年5月的使用LR-115 II型探测器完成，由法国柯达州柯达·帕特制造。 为了减少气象参数的影响，已经使用了统计分析工具，例如多元线性回归和人工神经网络。 在观察期间发生的一些地震之前记录氡浓度的降低。 还记录了一些假异构体，其可能归因于持续的地壳变形，这不足以产生地震。

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