Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula

Knowledge-Based Systems

Volumn 50, Issue , 2013, Pages 198-210

  Martinez Alvarez F ^a   Reyes, J ^b   Morales Esteban, A ^c   Rubio Escudero, C ^c  

^a UNIVERSIDAD PABLO DE OLAVIDE   (Spain)

^b TGT NT2 Labs   (Chile)

^c UNIVERSITY OF SEVILLE   (Spain)

Author keywords

Earthquake prediction; Feature selection; Seismicity indicators; Supervised classification; Time series

Indexed keywords

EARTHQUAKE PREDICTION; IBERIAN PENINSULA; LEARNING CLASSIFIERS; MULTIPLE INDICATORS; PREDICTION METHODS; PREDICTION PROBLEM; SELECTION TECHNIQUES; SUPERVISED CLASSIFICATION;

EARTHQUAKES; FEATURE EXTRACTION; LEARNING SYSTEMS; NEURAL NETWORKS; OPTIMIZATION; TIME SERIES;

FORECASTING;

EID: 84881312001     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2013.06.011     Document Type: Article

References (53)

1. H. Adeli, and A. Panakkat A probabilistic neural network for earthquake magnitude prediction Neural Networks 22 2009 1018 1024
2. A.S.N. Alarifi, N.S.N. Alarifi, and S. Al-Humidan Earthquakes magnitude predication using artificial neural network in northern Red Sea area Journal of King Saud University - Science 24 2012 301 313
3. C.R. Allen Responsibilities in earthquake prediction Bulletin of the Seismological Society of America 66 1982 2069 2074
4. E.I. Alves Earthquake forecasting using neural networks: results and future work Nonlinear Dynamics 44 1-4 2006 341 349
5. M. Anad, A. Dash, M.S.J. Kumar, and A. Kesarkar Prediction and classification of thunderstorms using artificial neural network International Journal of Engineering Science and Technology 3 5 2011 4031 4035
6. A. Arauzo-Azofra, J.L. Aznarte, and J.M. Benítez Empirical study of feature selection methods based on individual feature evaluation for classification problems Expert Systems with Applications 38 7 2007 8170 8177
7. M. Bose, F. Wenzel, and M. Erdik PreSIS: a neural network-based approach to earthquake early warning for finite faults Bulletin of the Seismological Society of America 98 1 2008 366 382
8. G. Box, and G. Jenkins Time Series Analysis: Forecasting and Control 2008 John Wiley and Sons
9. G. Chattopadhyay, and S. Chattopadhyay Dealing with the complexity of earthquake using neurocomputing techniques and estimating its magnitudes with some low correlated predictors Arabian Journal of Geosciences 2 3 2009 247 255
10. C. Cortes, and V. Vapnik Support-vector networks Machine Learning 20 3 1995 273 297
11. T.M. Cover, and P.E. Hart Nearest neighbor pattern classification IEEE Transactions on Information Theory 13 1 1967 21 27
12. M. D'Arco, A. Liccardo, and N. Pasquino ANOVA-based approach for DAC diagnostics IEEE Transactions on Instrumentation and Measurement 61 7 2012 1874 1882
13. C.S. Dhir, N. Iqbal, Y. Soo-Young, Efficient feature selection based on information gain criterion for face recognition, in: Proceedings of the IEEE International Conference on Information Acquisition, 2007, pp. 523-527.
14. J.E. Ebel, D.W. Chambers, A.L. Kafka, and J.A. Baglivo Non-poissonian earthquake clustering and the hidden Markov model as bases for earthquake forecasting in California Seismollogical Research Letters 78 1 2007 57 65
15. D.A. Freedman Statistical Models: Theory and Practice 2005 Cambridge University Press
16. S. García, A. Fernández, J. Luengo, and F. Herrera A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability Soft Computing 13 10 2009 959 977
17. Y. Han, and L. Yu A variance reduction framework for stable feature selection Statistical Analysis and Data Mining 5 5 2012 428 445
18. D.J. Hand, and K. Yu Idiot's Bayes - not so stupid after all? International Statistical Review 69 3 2001 385 399
19. N. Houlié, J.C. Komorowski, M. de Michele, M. Kasereka, and H. Ciraba Early detection of eruptive dykes revealed by normalized difference vegetation index (NDVI) on Mt. Etna and Mt. Nyiragongo Earth and Planetary Science Letters 246 3-4 2006 231 240
20. Spanish's National Geographical Institute, < http://www.ign.es >.
21. A. Jiménez, A.M. Posadas, and K.F. Tiampo Describing seismic pattern dynamics by means of using cellular automata Lecture Notes in Earth Sciences 112 2008 273 290
22. P. Kamatchi, K.B. Rao, N.R. Iyer, and S. Arunachalam Neural network-based methodology for inter-arrival times of earthquakes Natural Hazards 64 2 2012 1291 1303
23. T. Kohonen Self-organized formation of topologically correct feature maps Biological Cybernetics 43 1986 59 69
24. I. Koprinska Feature selection for brain-computer interfaces Lecture Notes in Artificial Intelligence 5669 2010 100 111
25. F. Kulahci, M. Inceoz, M. Dogru, E. Aksoy, and O. Baykara Artificial neural network model for earthquake prediction with radon monitoring Applied Radiation and Isotopes 67 1 2009 212 220
26. M. Moustra, M. Avraamides, and C. Christodoulou Artificial neural networks for earthquake prediction using time series magnitude data or seismic electric signals Expert Systems with Applications 38 12 2011 15032 15039
27. R. Madahizadeh, and M. Allamehzadeh Prediction of aftershocks distribution using artificial neural networks and its application on the May 12, 2008 Sichuan earthquake Journal of Seismology and Earthquake Engineering 11 3 2009 111 120
28. F. Martínez-Álvarez, A. Troncoso, A. Morales-Esteban, and J.C. Riquelme Computational intelligence techniques for predicting earthquakes Lecture Notes in Artificial Intelligence 6679 2 2011 287 294
29. M. Martínez-Ballesteros, F. Martínez-Álvarez, A. Troncoso, and J.C. Riquelme An evolutionary algorithm to discover quantitative association rules in multidimensional time series Soft Computing 15 10 2011 2065 2084
30. A. Morales-Esteban, F. Martínez-Álvarez, and J. Reyes Earthquake prediction in seismogenic areas of the Iberian Peninsula based on computational intelligence Tectonophysics 593 2013 121 134
31. A. Morales-Esteban, F. Martínez-Álvarez, A. Troncoso, J.L. de Justo, and C. Rubio-Escudero Pattern recognition to forecast seismic time series Expert Systems with Applications 37 12 2010 8333 8342
32. K.Z. Nanjo, J.R. Holliday, C.C. Chen, J.B. Rundle, and D.L. Turcotte Application of a modified pattern informatics method to forecasting the locations of future large earthquakes in the central Japan Tectonophysics 424 2006 351 366
33. University of Chile, National Service of Seismology, < http://ssn.dgf.uchile.cl/seismo.html >.
34. WEKA The University of Waikatu, Data mining with open source machine learning software in Java, < http://www.cs.waikato.ac.nz/ml/weka/ >.
35. A. Panakkat, and H. Adeli Neural network models for earthquake magnitude prediction using multiple seismicity indicators International Journal of Neural Systems 17 1 2007 13 33
36. A. Panakkat, and H. Adeli Recent efforts in earthquake prediction (1990-2007) Natural Hazards Review 9 2 2008 70 80
37. A. Panakkat, and H. Adeli Recurrent neural network for approximate earthquake time and location prediction using multiple sesimicity indicators Computer-Aided Civil and Infrastructure Engineering 24 2009 280 292
38. K. Ramar, T.T. Mirnalinee, An ontological representation for tsunami early warning system, in: Proceedings of the IEEE International Conference on Advances in Engineering, Science and Management, 2012, pp. 93-98.
39. J. Reyes, and V. Cárdenas A Chilean seismic regionalization through a Kohonen neural network Neural Computing and Applications 19 2010 1081 1087
40. J. Reyes, A. Morales-Esteban, and F. Martínez-Álvarez Neural networks to predict earthquakes in Chile Applied Soft Computing 13 2 2013 1314 1328
41. R. Romero-Záliz, C. Rubio-Escudero, I. Zwir, and C. del Val Optimization of multi-classifiers for computational biology: application to gene finding and expression Theoretical Chemistry Accounts: Theory Computation and Modeling 125 3 2010 599 611
42. R. Ruiz, J.C. Riquelme, and J.S. Aguilar-Ruiz Incremental wrapper-based gene selection from microarray expression data for cancer classification Pattern Recognition 39 12 2006 2383 2392
43. C. Shang, D. Barnes, Support vector machine-based classification of rock texture images aided by efficient feature selection, in: Proceedings of the IEEE International Joint Conference on Neural Networks, 2012, pp. 1-8.
44. S. Srilakshmi, and R.K. Tiwari Model dissection from earthquake time series: a comparative analysis using nonlinear forecasting and artificial neural network approach Computers and Geosciences 35 2009 191 204
45. Y. Su, J. Dai, X. Liu, Q. Xu, Y. Zhuang, W. Chen, and X. Zheng EEG channel evaluation and selection by rough set in P300 BCI Journal of Computational Information Systems 6 6 2010 1727 1735
46. W. Sun, S. Shan, C. Zhang, P. Ge, L. Tao, Prediction of typhoon losses in the South-East of China based on B-P network, in: Proceedings of the IEEE International Conference on Artificial Intelligence and Computational Intelligence, 2010, pp. 252-256.
47. K.F. Tiampo, and R. Shcherbakov Seismicity-based earthquake forecasting techniques: ten years of progress Tectonophysics 522-523 2012 89 121
48. Y. Toya, K.F. Tiampo, J.B. Rundle, C.C. Chen, and W. Klein Pattern informatics approach to earthquake forecasting in 3D Concurrency and Computation: Practice and Experience 22 2010 1569 1592
49. C. Wang The study on the spam filtering technology based on Bayesian algorithm International Journal of Computer Science Issues 10 3 2013 668 675
50. Y. Wang, I.H. Witten, Induction of model trees for predicting continious classes, in: Proceedings of the European Conference on Machine Learning, Praga, 1997, pp. 128-137.
51. A. Zamani, M.R. Sorbi, and A.A. Safavi Application of neural network and ANFIS model for earthquake occurrence in Iran Earth Science Informatics 6 2 2013 71 85
52. F. Zhang The future of hurricane prediction Computing in Science and Engineering 13 1 2011 9 12
53. Z. Zheng, X. Wu, and R. Shihari Feature selection for text categorization on imbalanced data ACM SIGKDD Explorations Newsletter 6 1 2004 80 89