Logistic regression and neural network classification of seismic records

International Journal of Rock Mechanics and Mining Sciences

Volumn 62, Issue , 2013, Pages 86-95

  Vallejos, J A ^a,b,c   McKinnon, S D ^a  

^a QUEEN S UNIVERSITY   (Canada)

^b UNIVERSITY OF CHILE   (Chile)

^c UNIVERSITY OF CHILE   (Chile)

Author keywords

Blast; Classification of seismic records; Mine safety; Mining seismicity; Re entry protocol; Rockbursts

Indexed keywords

ABILITY TESTING; CLASSIFICATION (OF INFORMATION); STATISTICAL TESTS;

BLAST; CLASSIFICATION OF SEISMIC RECORD; LOGISTIC NETWORK MODELING; LOGISTICS REGRESSIONS; MINE SAFETY; MINING SEISMICITY; NEURAL NETWORK CLASSIFICATION; NEURAL NETWORK MODEL; RE-ENTRY PROTOCOL; SEISMIC RECORDS;

REGRESSION ANALYSIS;

ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; FREQUENCY-MAGNITUDE DISTRIBUTION; MATRIX; MINE; REGRESSION ANALYSIS; ROCK MECHANICS; SAFETY; SEISMICITY;

CANADA; ONTARIO [CANADA];

EID: 84878439541     PISSN: 13651609     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijrmms.2013.04.005     Document Type: Article

References (14)

1. Vallejos JA, McKinnon SD. Omori's law applied to mining-induced seismicity and re-entry protocol development. Pure Appl Geophys 2010, 167(1):91-106.
2. Vallejos J.A., McKinnon S.D Correlations between mining and seismicity for re-entry protocol development. International Journal of Rock Mechanics and Mining Sciences 2011, 48(4):616-625.
3. Vallejos JA, McKinnon SD. Guidelines for development of re-entry protocols in seismically active mines. In: Proceeding of the 42nd US Rock mechanics symposium, San Francisco, CA, ARMA/USRMS; 2008. paper 08-97.
4. Vasak P. Full-waveform microseismic monitoring. CAMIRO project #11-full wave implementation. Report to the Technical Advisory Committee of the Canadian Mining Industry Research Organization, Mining Division 1999, 109. Neumann Engineering and Mining Services Inc, Kingston, ON.
5. Urbancic TI, Trifu C-I, Mercer RA, Feustel AJ. Alexaner JAG. automatic time-domain calculation of source parameters for the analysis of Induced seismicity. Bull Seismol Soc Am 1996, 86(5):1627-1633.
6. Hosmer DW, Lemeshow S. Applied Logistic Regression 1989, Wiley Interscience, New York.
7. Menard S. Applied logistic regression analysis. Sage University paper series on quantitative applications in social science; 2002. p. 106.
8. Duda RO, Hart PE, Stork DG. Pattern classification 2000, Wiley Interscience, New York.
9. Fawcett T. An introduction to ROC analysis. Pattern Recog Lett 2006; 27:861-74.
10. Masters T. Advanced algorithms for neural networks 1995, Wiley Interscience, New York.
11. Heidke P. Berechnung des Erfolges und der Güte der Windstärkevorhersagen im Sturmwarnungsdienst. Geogr Ann 1926, 8:301-349. In German.
12. Peirce C.S. The numerical measure of the success of predictions. Science 1884, 4:453-454.
13. Basheer IA, Hajmeer M. Artificial neural networks: fundamentals, computing, design, and application. J Microbiol Meth 2000, 43:3-31.
14. NeuralWorks. NeuralWare frequently asked questions-Technical support,; 2009. http://www.neuralware.com/support_faq.jsp#proq3.