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Application of Neural Network With New Hybrid Algorithm in Volcanic Rocks Seismic Prediction

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  • Yanchao Liu

    (School of Automation, Baotou Light Industry Vocational Technical College, Baotou, China)

  • Limei Yan

    (College of Electrical Information Engineering, Northeast Petroleum University, Daqing, China)

  • Jianjun Xu

    (College of Electrical Information Engineering, Northeast Petroleum University, Daqing, China)

Abstract

This article has studied the application design and implementation of neural network with new hybrid algorithm in volcanic rocks prediction. It is considered that the convergence rate of EBP algorithm is slow, and the local minimum value can be obtained by EBP algorithm, and the approximation of global optimal value can be obtained by EBP algorithm. Therefore, genetic algorithm and EBP algorithm are proposed. The weight of the multilayer feed-forward neural network is determined by using the genetic BP algorithm. The new hybrid algorithm is applied to the neural network and volcanic oil and gas identification and compared with the traditional BP neural network. In contrast, using the new hybrid genetic algorithm to calculate the neural network is very small; you can quickly get the global optimal value.

Suggested Citation

  • Yanchao Liu & Limei Yan & Jianjun Xu, 2018. "Application of Neural Network With New Hybrid Algorithm in Volcanic Rocks Seismic Prediction," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 12(4), pages 55-68, October.
    • Handle: RePEc:igg:jcini0:v:12:y:2018:i:4:p:55-68
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