Advertisement

A Novel Bio Inspired Algorithm Based on Echolocation Mechanism of Bats for Seismic Hazards Detection

  • Mohamed Elhadi RahmaniEmail author
  • Abdelmalek Amine
  • Reda Mohamed Hamou
  • Amine Rahmani
  • Hanane Menad
  • Hadj Ahmed Bouarara
  • Mohamed Amine Boudia
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 1)

Abstract

Since the first birth of computers, a lot of works had done in many fields of computer science and inspired generations and generations of researches. Alan Turing pioneered researches by its works in heuristics, and now, hundreds of algorithms and approaches are developed in this field. The last two decades witnessed a very huge movement in field of artificial intelligence. Researchers went far than invention of algorithms based on calculation, they created Bio inspired algorithms which are sort of implementation of natural solutions to solve hard problems so called NP problems. This paper presents a new bio inspired algorithm based in the echolocation behaviour of bats for seismic hazard prediction in coal mines. The implementation of the algorithm includes three fields of studies, data discovery or so called data mining, bio inspired techniques, and seismic hazards predictions.

Keywords

Seismic hazards detection Data mining Meta heuristic Bio inspired algorithm Bat echolocation Machine learning 

References

  1. 1.
    Kabiesz, J.: Effect of the form of data on the quality of mine tremors hazard forecasting using neural networks. Geotech. Geol. Eng. 24(5), 1131–1147 (2006)CrossRefGoogle Scholar
  2. 2.
    Yang, X.S., He, X.: Bat algorithm: literature review and applications. Int. J. Bio-Inspired Comput. 5(3), 141–149 (2013)CrossRefGoogle Scholar
  3. 3.
    Gale, W.J., Heasley, K.A., Iannacchione, A.T., Swanson, P.L., Hatherly, P., King, A.: Rock damage characterisation from microseismic monitoring. In: DC Rocks 2001, The 38th US Symposium on Rock Mechanics (USRMS). American Rock Mechanics Association (2001)Google Scholar
  4. 4.
    Gibowicz, S.J., Lasocki, S.: Seismicity induced by mining: ten years later. Adv. Geophys. 44, 39–181 (2001)CrossRefGoogle Scholar
  5. 5.
    Kornowski, J.: Linear prediction of aggregated seismic and seismoacoustic energy emitted from a mining longwall. ACTA MONTANA 129, 5–14 (2003)Google Scholar
  6. 6.
    Lasocki, S.: Probabilistic analysis of seismic hazard posed by mining induced events. In: Proceedings of 6th International Symposium on Rockburst in Mines Controlling Seismic Risk. ACG, Perth, pp. 151–156 (2005)Google Scholar
  7. 7.
    Rudajev, V., Ciz, R.: Estimation of mining tremor occurrence by using neural networks. Pure Appl. Geophys. 154(1), 57–72 (1999)Google Scholar
  8. 8.
    Makwka, J., Kabiesz, J.: Prediction of sites and energy of seismic tremorsmethods and results. In: Proceedings of the Conference Mining Natural Hazards. Ustron (2005)Google Scholar
  9. 9.
    Leniak, A., Isakow, Z.: Spacetime clustering of seismic events and hazard assessment in the Zabrze-Bielszowice coal mine, Poland. Int. J. Rock Mech. Min. Sci. 46(5), 918–928 (2009)CrossRefGoogle Scholar
  10. 10.
    Bodri, B.: A neural-network model for earthquake occurrence. J. Geodyn. 32(3), 289–310 (2001)CrossRefGoogle Scholar
  11. 11.
    Sikora, M.: Induction and pruning of classification rules for prediction of microseismic hazards in coal mines. Expert Syst. Appl. 38(6), 6748–6758 (2011)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Yang, X.S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pp. 65–74. Springer, Berlin (2010)Google Scholar
  13. 13.
    Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques (2011)Google Scholar
  14. 14.
    Sammut, C., Webb, G.I. (eds.): Encyclopedia of Machine Learning. Springer (2011)Google Scholar
  15. 15.
    Vuk, M., Curk, T.: ROC curve, lift chart and calibration plot. Metodoloski zvezki 3(1), 89–108 (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mohamed Elhadi Rahmani
    • 1
    Email author
  • Abdelmalek Amine
    • 1
  • Reda Mohamed Hamou
    • 1
  • Amine Rahmani
    • 1
  • Hanane Menad
    • 1
  • Hadj Ahmed Bouarara
    • 1
  • Mohamed Amine Boudia
    • 1
  1. 1.GeCoDe Laboratory, Department of Computer ScienceUniversity of Dr. Tahar MoulaySaidaAlgeria

Personalised recommendations