Abstract
Earthquakes are natural disasters which may result in heavy losses. Accurate prediction of the time and intensity of future earthquakes can lead to minimizing losses due to earthquakes. A number of earthquake predictions have been proposed based on mathematical and statistical models. In this paper, we present an earthquake prediction technique using Bat Algorithm (BA) and Feed Forward Neural Network (FFNN). The BA is used to train the weights of the FFNN to predict future earthquakes on the basis of past input data. Experimental results show that our proposed approach is highly comparable and more stable than Back Propagation Neural Network (BPNN) with respect to accuracy.
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Adeli H, Panakkat A (2009) A probabilistic neural network for earthquake magnitude prediction. J Neural Netw 22(7)
Akhoondzadeh M (2014) Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan, Iran, (Mw = 7.7) earthquake of 16 April 2013. Adv Space Res 53:647–655
Alarifi ASN, Alarifi NSN, Al-Humidan S (2012) Earthquakes magnitude predication using artificial neural network in northern Red Sea area. J King Saud Univ Sci 24:301–313
Alavi AH, Gandomi AH (2011) Prediction of principal ground-motion parameters using a hybrid method coupling artificial neural networks and simulated annealing. Comp Struct 89:2176–2194
Bodri B (2001) A neural-network model for earthquake occurrence. J Geodyn 32:289–310
Deep K, Yadav A, Kumar S (2012) Improving local and regional earthquake locations using an advance inversion technique: particle swarm optimization. World J Model Simul 8(2):135–141
Deep K, Yadav A, Kumar S (2011) Determining earthquake locations in NW Himalayan region: an application of particle swarm optimization. Int J Comput Sci Math 3(2):173–181 (ISSN 0974–3189)
Dehbozorgi L, Farokhi F (2010) Effective feature selection for short-term earthquake prediction using neuro-fuzzy classifier. In: 2010 Second IITA International Conference on Geoscience and Remote Sensing
Khan K, Sahai A (2012) A comparison of BA, GA, PSO, BP and LM for training feed forward neural networks in e-learning context. IJISA 4(7):23–29
Liu Y, Liu H, Zhang B, Wu G (2004) Extraction of if-then rules from trained neural network and its application to earthquake prediction. In: Proceedings of the Third IEEE International Conference on Cognitive Informatics (ICCI’04)
Moustra M, Avraamides M, Christodoulou C (2011) Artificial neural networks for earthquake prediction using time series magnitude data or Seismic Electric Signals. Exp Syst Appl 38:15032–15039
Prakash D (2012) Bespoke artificial Bee Colony Algorithm to determine the earthquake locations. Adv Mech Eng its Appl (AMEA) 2(3):207 (ISSN 2167–6380)
Preethi G, Santhi B (2011) Study on techniques of earthquake prediction. Int J Comp Appl 29(4) (0975–8887)
Shah H, Ghazali R, Nawi NM (2011) Using artificial bee colony algorithm for MLP training on earthquake time series data prediction. arXiv:1112.4628
SU YP, ZHU QJ (2009) Application of ANN to prediction of earthquake influence. In: Second International Conference on Information and Computing Science
Suratgar AA, Setoudeh F, Salemi AH (2008) Magnitude of earthquake prediction using neural network. In: Fourth International Conference on Natural Computation IEEE. doi:10.1109/ICNC.2008.781
US geological survey hazards program website. earthquake.usgs.gov/Retrieved 2013-6-10
Yang XS (2010) A new meta-heuristic bat-inspired algorithm. In: Gonzalez JR et al. (eds) Nature Inspired Co-operative Strategies for Optimization (NISCO 2010), Studies in Computational Intelligence, Springer, Berlin, vol 284, pp 65–74
Ying W, Yi C, Jinkui Z (2009) The application of RBF neural network in earthquake prediction. In: 2009 Third International Conference on Genetic and Evolutionary Computing. doi:10.1109/WGEC.2009.81
Zamani AS, Al-Arifi NS, Khan S (2012) Response prediction of earthquake motion using artificial neural networks. IJAR-CSIT
Zhang Q, Wang C (2008) Using genetic algorithm to optimize artificial neural network: a case study on earthquake prediction. In: Second International Conference on Genetic and Evolutionary Computing. doi:10.1109/WGEC.2008.96
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Saba, S., Ahsan, F. & Mohsin, S. BAT-ANN based earthquake prediction for Pakistan region. Soft Comput 21, 5805–5813 (2017). https://doi.org/10.1007/s00500-016-2158-2
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DOI: https://doi.org/10.1007/s00500-016-2158-2