The possible of Earthquake prediction In Thailand with Artificial Neural Network models.
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Published:
Aug 20, 2021
Keywords:
Artificial Neural Network Model Earthquake Prediction
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Abstract
Earthquake prediction with artificial neural network model (ANN) has never been studied in Thailand before. However, after searching research article from international database, it has been found that there is possibility to use ANN model to predict earthquake in other countries. Therefore, this article is about to study the possibility to predict earthquakes with ANN in Thailand and to collect earthquake data. In addition, the scopes of this study are three points; (1) The earthquakes pattern in Thailand mainly caused by the movement of the active fault, also the magnitude of the earthquake and the increasing trend of earthquake rate, had a similar pattern of the occurrence to other countries by analyzing the earthquake prediction with the artificial neural network model. (2) The input variables are obtained from the Gutenberg-Richter equation, which is the most input variables to be considered. The most popular output variable for earthquake prediction is the earthquake’s magnitude. (3) The architectural structure design of the model mainly used Feed Forward Neural Network with Back Propagation Learning and the number of hidden nodes with good performance is ANN model with two hidden layers, also the number of hidden nodes depend on the input variables of ANN.
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References
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2. Jiang M. Easily magnetic anomalies earthquake prediction. MATEC Web of Conferences 2016;63:1-5.
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4. Guo G, Jie Y. Three Attempts of Earthquake Prediction with Satellite Cloud Images. Natural Hazards and Earth System Sciences 2013;13:91-5.
5. Jilani Z, Mehmood T, Alam A, Awais M, Iqbal T. Monitoring and descriptive analysis of radon in relation to seismic activity of Northern Pakistan. Journal of Environmental Radioactivity 2017;172:43-51.
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7. Kannan S. Innovative Mathematical Model for Earthquake Prediction. Engineering Failure Analysis 2014;41:89-95.
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11. Reyes J, Morales-Esteban A, Martínez- Álvarez F. Neural networks to predict earthquakes in Chile. Applied Soft Computing 2013;13(2):1314-28.
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21. Adeli H, Panakkat A. A probabilistic neural network for earthquake magnitude prediction. Neural Networks. 2009;22(7):1018-24.
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24. Narayanakumar S, Raja K. A BP Artificial Neural Network Model for Earthquake Magnitude Prediction in Himalayas, India. Circuits and Systems 2016;7(11):3456-68.
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29. Sil A, Zarola A. Artificial neural networks (ANN) and stochastic techniques to estimate earthquake occurrences in Northeast region of India. Annals of Geophysics 2017:1-37.
30. Morales-Esteban A, Martínez-Álvarez F, Reyes J. Earthquake prediction in seismogenic areas of the Iberian Peninsula based on computational intelligence. Tectonophysics 2013;593:121-34.
31. Zollo A, Marzocchi W, Capuano P, Lomax A, Iannaccone G. Space and time behavior of seismic activity at Mt. Vesuvius volcano, Southern Italy 2002:625-40.
32. Shi Y, Bolt. The standard error of the Magnitude-frequency b value. Bulletin of the Seismological Society of America 1982;72(5):1677-87.
33. Moustra M, Avraamides M, Christodoulou C. Artificial neural networks for earthquake prediction using time series magnitude data or Seismic Electric Signals. Expert Systems with Applications 2011;38(12):15032-9.
34. Zhou F, Zhu X. Earthquake Prediction Based on LM-BP Neural Network. Lecture Notes in Electrical Engineering. 2014;270:13-20.
35. Bhatia A, Pasari S, Mehta A. Earthquake Forecasting Using Artificial Neural Networks. International Archives of the Photogrammetry, Remte Sensing & Spatial Information Sciences 2018:823-7.
36. Zhang Q, Wang C. Using Genetic Algorithm to Optimize Artificial Neural Network: A Case Study on Earthquake Prediction. IEEE 2008:128-31.
37. Martínez-Álvarez F, Reyes J, Morales-Esteban A, Rubio-Escudero C. Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula. Knowledge-Based Systems 2013;50:198-210.
38. Buscema M, Massini G, Maurelli G. Artificial Adaptive Systems to predict the magnitude of earthquakes. Bollettino di Geofisica Teorica ed Applicata 2015;56(2):227-56.
39. Niksarlioglu S, Kulahci F. An Artificial Neural Network Model for Earthquake Prediction and Relations between Environmental Parameters and Earthquakes. WAS Engineering and Technology 2013;7(2):87-92.
40. Alarifi ASN, Alarifi NSN, Al-Humidan S. Earthquakes magnitude predication using artificial neural network in northern Red Sea area. Journal of King Saud University – Science 2012;24(4):301-13.
41. Soleimani Zakeri NS, Pashazadeh S. Application of Neural Network Based on Genetic Algorithm in Predicting Magnitude of Earthquake in North Tabriz Fault (NW Iran). Current Science 2015;109(9):1715-22.
42. กรมป้องกัน และ บรรเทาสาธารณภัย. 2556. การลดความเสี่ยงจากสาธารณภัย. กรุงเทพฯ: โรงพิมพ์ชุมนุมสหกรณ์การเกษตรแห่งประเทศไทย จำกัด.
43. รายงานการเกิดแผ่นดินไหวบริเวณจังหวัดเชียงราย. สำนักเฝ้าระวังแผ่นดินไหว กรมอุตุนิยมวิทยา,2557.
44. ลักษณะเฉพาะของรูปแบบไหวสะเทือนบริเวณชายแดนประเทศไทย-ลาว-พม่า. สำนักเฝ้าระวังแผ่นดินไหว กรมอุตุนิยมวิทยา, 2560.
45. Negarestani A, Setayeshi S, Ghannadi-Maragheh M, Akashe B. Layered neural networks based analysis of radon concentration and environmental parameters in earthquake prediction. Journal of Environmental Radioactivity 2002;62(3):225-33.
46. Plumb AP, Rowe RC, York P, Brown M. Optimisation of the predictive ability of artificial neural network (ANN) models: a comparison of three ANN programs and four classes of training algorithm. Eur J Pharm Sci 2005;25 (4-5):395-405.
2. Jiang M. Easily magnetic anomalies earthquake prediction. MATEC Web of Conferences 2016;63:1-5.
3. Hayakawa M. Electromagnetic phenomena related with earthquakes (earthquake prediction). The International Workshop on Modern Science and Technology 2008:393-8.
4. Guo G, Jie Y. Three Attempts of Earthquake Prediction with Satellite Cloud Images. Natural Hazards and Earth System Sciences 2013;13:91-5.
5. Jilani Z, Mehmood T, Alam A, Awais M, Iqbal T. Monitoring and descriptive analysis of radon in relation to seismic activity of Northern Pakistan. Journal of Environmental Radioactivity 2017;172:43-51.
6. Yamauchi H, Uchiyama H, Ohtani N, Ohta M. Unusual Animal Behavior Preceding the 2011 Earthquake off the Pacific Coast of Tohoku, Japan: A Way to Predict the Approach of Large Earthquakes. Animals 2014;4(2):131-45.
7. Kannan S. Innovative Mathematical Model for Earthquake Prediction. Engineering Failure Analysis 2014;41:89-95.
8. Sheng J, Mu D, Zhang H, Lv H. Seismotectonics Considered Artificial Neural Network Earthquake Prediction in Northeast Seismic Region of China. The Open Civil Engineering Journal 2015;9:522-8.
9. Sriram A, Rahanamayan S, Bourennani F. Artificial Neural Networks for Earthquake Anomaly Detection. Journal of Advanced Computational Intelligence and Intelligent Informatics 2014;18(5):701-13.
10. Emilio Florido, José L. Aznarte, Antonio Morales-Esteban, Martínez-Álvarez F. Earthquake magnitude prediction based on articial neural networks: A survey. Croatian Operational Research. 2016;7:159-69.
11. Reyes J, Morales-Esteban A, Martínez- Álvarez F. Neural networks to predict earthquakes in Chile. Applied Soft Computing 2013;13(2):1314-28.
12. Cortés G, Martínez-Álvarez F, Troncoso A, Morales-Esteban A. Medium-large earthquake magnitude prediction in Tokyo with artificial neural networks. Neural Comput & Applic 2017:1043-55.
13. Wang Q, Guo Y, Yu L, Li P. Earthquake Prediction based on Spatio-Temporal Data Mining: An LSTM Network Approach. IEEE Transactions on Emerging Topics in Computing 2019:1-11.
14. Nanjo K, Holliday J, Chen C-C, Rundle J, Turcotte DL. Application of a modified pattern informatics method to forecasting the locations of future large earthquakes in the central Japan. Tectonophysics 2006;424:351-66.
15. Li C, Liu X. An improved PSO-BP neural network and its application to earthquake prediction. In Proceedings of the Chinese Control and Decision Conference 2016:3434-8.
16. Shah H, Ghazali R, Mohd Nawi N. Using Artificial Bee Colony Algorithm for MLP Training on EarthquakeTime Series Data Prediction. Second International Conference on Genetic and Evolutionary Computing 2011:128-31.
17. Shao X, Li X, Li L, Hu X. The Application of Ant-Colony Clustering Algorithm to Earthquake Prediction. Advances in Electronic Engineering,Communication and Management 2012:145-50.
18. Zamani A, Sorbi M, Safavi AA. Application of neural network and ANFIS model for earthquake occurrence in Iran. Earth Sci Inform 2013:71-85.
19. Külahcı F, Inceöz M, Dogru M, Aksoy E, Baykara O. Artificial neural network model for earthquake prediction with radon monitoring. Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture. industry and medicine 2008;67:212-9.
20. Panakkat A, Adeli H. Recurrent Neural Network for Approximate Earthquake Time and Location Prediction Using Multiple Seismicity Indicators. Computer-Aided Civil and Infrastructure Engineering 2009;24:280-92.
21. Adeli H, Panakkat A. A probabilistic neural network for earthquake magnitude prediction. Neural Networks. 2009;22(7):1018-24.
22. Madahizadeh R, Allamehzadeh M. Prediction of Aftershocks Distribution Using Artificial Neural Networks and Its Application on the May 12, 2008 Sichuan Earthquake. Journal of Seismology and Earthquake Engineering. 2009;11:111-20.
23. Spall H. Clarence Allen talks about the responsibilities in earthquake prediction. Earthquake Information Bulletin (USGS) 1978;10(4):116-9.
24. Narayanakumar S, Raja K. A BP Artificial Neural Network Model for Earthquake Magnitude Prediction in Himalayas, India. Circuits and Systems 2016;7(11):3456-68.
25. Abraham A, V R. A Particle Swarm Optimization - Backpropagation (PSO-BP) Model for the Prediction of Earthquake in Japan. In: Shetty NR et al (ed) Emerging Research in Computing, Information, Communication and Applications. Advances in Intelligent Systems and Computing 2009;882:435-41.
26. Panakkat A, Adeli H. Neural Network Models for earthquake Magnitude Prediction Using Multipl Seismicity Indicators. International Journal of Neural Systems 2007;17(01):13-33.
27. Sunkara S, Tiwari RK. Model dissection from earthquake time series: A comparative analysis using modern non-linear forecasting and artificial neural network approaches 2009:191-204.
28. Bodri B. A neural network model for earthquake occurrence. Journal of Geodynamics 2001;32(3):289-310.
29. Sil A, Zarola A. Artificial neural networks (ANN) and stochastic techniques to estimate earthquake occurrences in Northeast region of India. Annals of Geophysics 2017:1-37.
30. Morales-Esteban A, Martínez-Álvarez F, Reyes J. Earthquake prediction in seismogenic areas of the Iberian Peninsula based on computational intelligence. Tectonophysics 2013;593:121-34.
31. Zollo A, Marzocchi W, Capuano P, Lomax A, Iannaccone G. Space and time behavior of seismic activity at Mt. Vesuvius volcano, Southern Italy 2002:625-40.
32. Shi Y, Bolt. The standard error of the Magnitude-frequency b value. Bulletin of the Seismological Society of America 1982;72(5):1677-87.
33. Moustra M, Avraamides M, Christodoulou C. Artificial neural networks for earthquake prediction using time series magnitude data or Seismic Electric Signals. Expert Systems with Applications 2011;38(12):15032-9.
34. Zhou F, Zhu X. Earthquake Prediction Based on LM-BP Neural Network. Lecture Notes in Electrical Engineering. 2014;270:13-20.
35. Bhatia A, Pasari S, Mehta A. Earthquake Forecasting Using Artificial Neural Networks. International Archives of the Photogrammetry, Remte Sensing & Spatial Information Sciences 2018:823-7.
36. Zhang Q, Wang C. Using Genetic Algorithm to Optimize Artificial Neural Network: A Case Study on Earthquake Prediction. IEEE 2008:128-31.
37. Martínez-Álvarez F, Reyes J, Morales-Esteban A, Rubio-Escudero C. Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula. Knowledge-Based Systems 2013;50:198-210.
38. Buscema M, Massini G, Maurelli G. Artificial Adaptive Systems to predict the magnitude of earthquakes. Bollettino di Geofisica Teorica ed Applicata 2015;56(2):227-56.
39. Niksarlioglu S, Kulahci F. An Artificial Neural Network Model for Earthquake Prediction and Relations between Environmental Parameters and Earthquakes. WAS Engineering and Technology 2013;7(2):87-92.
40. Alarifi ASN, Alarifi NSN, Al-Humidan S. Earthquakes magnitude predication using artificial neural network in northern Red Sea area. Journal of King Saud University – Science 2012;24(4):301-13.
41. Soleimani Zakeri NS, Pashazadeh S. Application of Neural Network Based on Genetic Algorithm in Predicting Magnitude of Earthquake in North Tabriz Fault (NW Iran). Current Science 2015;109(9):1715-22.
42. กรมป้องกัน และ บรรเทาสาธารณภัย. 2556. การลดความเสี่ยงจากสาธารณภัย. กรุงเทพฯ: โรงพิมพ์ชุมนุมสหกรณ์การเกษตรแห่งประเทศไทย จำกัด.
43. รายงานการเกิดแผ่นดินไหวบริเวณจังหวัดเชียงราย. สำนักเฝ้าระวังแผ่นดินไหว กรมอุตุนิยมวิทยา,2557.
44. ลักษณะเฉพาะของรูปแบบไหวสะเทือนบริเวณชายแดนประเทศไทย-ลาว-พม่า. สำนักเฝ้าระวังแผ่นดินไหว กรมอุตุนิยมวิทยา, 2560.
45. Negarestani A, Setayeshi S, Ghannadi-Maragheh M, Akashe B. Layered neural networks based analysis of radon concentration and environmental parameters in earthquake prediction. Journal of Environmental Radioactivity 2002;62(3):225-33.
46. Plumb AP, Rowe RC, York P, Brown M. Optimisation of the predictive ability of artificial neural network (ANN) models: a comparison of three ANN programs and four classes of training algorithm. Eur J Pharm Sci 2005;25 (4-5):395-405.