Conference Paper

A Fuzzy Logic Application for Explain Relationships Between 222Rn Concentration and Earthquakes

Volume: 39 Number: 1 March 16, 2018
TR EN

A Fuzzy Logic Application for Explain Relationships Between 222Rn Concentration and Earthquakes

Abstract

Earthquake behaviors are, in general, among the non-linear topics of physics. Unfortunately researches up to now could not yet propose a complete mathematical model for earthquake behavior prediction possibilities. The main reason for not being able to establish such a model is due to the non-linear behavior of the earthquake and its generation is dependent on a variety of indigenous factors. Mathematical expressions and modeling of the non-linear systems is comparatively difficult and sometimes requires high speed and memory computers. For this reason, the expert systems as Fuzzy Logic (FL) are now commonly used for such modelling. Model is suggested a system to examine the space-time behavior of any physical phenomena through a set of convenient mathematical expressions, which describe linear or non-linear aspects. Fuzzy logic applications have a fast increase in past few years. Fuzzy logic modelling can be a very powerful explains about internal structure of dynamic system. The most commonly used indicator in earthquake prediction studies is soil radon gas (222Rn). In this study, we have tried to explain relationships between 222Rn and earthquakes using fuzzy logic. The application region is performed for 222Rn data of Mersin region near the East Anatolian Fault System, Turkey.

Keywords

References

  1. [1]. Dragovic S., Antonije O., Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods. Appl Radiat Isotopes., 65 (2007) 218-224.
  2. [2]. Külahcı F., İnceöz M., Doğru M., Aksoy E., and Baykara O., Artificial neural network model for earthquake prediction with radon monitoring., Appl Radiat Isotopes, 67 (2009) 212–219.
  3. [3]. Gueldal V., Tongal H. Comparison of recurrent neural network, adaptive neuro-fuzzy inference system and stochastic models in Egirdir Lake level forecasting., Water Resour Manag, 24 (2010) 105-128.
  4. [4]. Zadeh L. A. Fuzzy sets. Information and Control, 8 (1967) 38-53.
  5. [5]. Şen, Z., Fuzzy Logic Principal and Modelling, (Engineering and Liberal art) p:11, Water Foundation Publication, İstanbul, 2009.
  6. [6]. Şen, Z., Scientific thinking and mathematical modeling principles p:11, Water Foundation Publication, İstanbul, 2009.
  7. [7]. Kisi O., Shiri J., Nikoofar B., Forecasting daily lake levels using artificial intelligence approaches., Comput Geosci,41 (2012) 169-180.
  8. [8]. Tarakçı, M., C. Harmanşah, M.M. Saç, and M. İçhedef (2014), Investigation of the relationships between seismic activities and radon level in Western Turkey, Appl. Radiat. Isotopes 83A, (2017) 12-17,

Details

Primary Language

English

Subjects

-

Journal Section

Conference Paper

Publication Date

March 16, 2018

Submission Date

December 2, 2017

Acceptance Date

January 31, 2018

Published in Issue

Year 2018 Volume: 39 Number: 1

APA
Kamışlıoğlu, M. (2018). A Fuzzy Logic Application for Explain Relationships Between 222Rn Concentration and Earthquakes. Cumhuriyet Science Journal, 39(1), 211-217. https://doi.org/10.17776/csj.360320

Cited By

As of 2026, Cumhuriyet Science Journal will be published in six issues per year, released in February, April, June, August, October, and December