Pure and Applied Geophysics

, Volume 174, Issue 7, pp 2793–2802 | Cite as

Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies

  • S. Singh
  • H. P. Jaishi
  • R. P. Tiwari
  • R. C. TiwariEmail author


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.


Radon measurements SSNTDs MLR and ANN analysis earthquake precursors statistical algorithm meteorological parameters 



This work has been funded by the Ministry of Earth Sciences (MoES), Govt. of India, New Delhi, in the form of Major project vide Sanction Order No. MoES/P.O.(Seismo)/1(167)/2013 dated 10.12.2013.


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Copyright information

© Springer International Publishing 2017

Authors and Affiliations

  • S. Singh
    • 1
  • H. P. Jaishi
    • 1
  • R. P. Tiwari
    • 2
  • R. C. Tiwari
    • 1
    Email author
  1. 1.Department of PhysicsMizoram UniversityAizawlIndia
  2. 2.Department of GeologyMizoram UniversityAizawlIndia

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