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Risk assessment of earthquake network public opinion based on global search BP neural network

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  • Xing Huang
  • Huidong Jin
  • Yu Zhang

Abstract

Background: The article proposes a network public opinion risk assessment model for earthquake disasters, which can provide an effective support for emergency departments of China. Method: It uses the accelerated genetic algorithm (AGA) to improve BP neural network. The main contents: This article selects 10 indexes by using the methods of the principal component analysis (PCA) and cumulative contribution (CC) to assess the risk of the earthquake network public opinion. The article designs a BP algorithm to measure the risk degree of the earthquake network public opinion and uses AGA to improve the BP model for parameter optimization. Results: The experiment results of the improved BP model shows that its global error is 7.12×10, and the error is reduced to 22.35%, which showed the improving BP model has advantages in convergence speed and evaluation accuracy. Conclusion: The risk assessment method of network public opinion can be used in the practice of earthquake disaster decision.

Suggested Citation

  • Xing Huang & Huidong Jin & Yu Zhang, 2019. "Risk assessment of earthquake network public opinion based on global search BP neural network," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-14, March.
    • Handle: RePEc:plo:pone00:0212839
    DOI: 10.1371/journal.pone.0212839
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    References listed on IDEAS

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    1. Lebensztayn, E. & Rodriguez, P.M., 2013. "A connection between a system of random walks and rumor transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5793-5800.
    2. Huang, Shihang & Liu, Ying & Dang, Depeng, 2014. "Burst topic discovery and trend tracing based on Storm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 331-339.
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    Cited by:

    1. Wei He & Yuan Fang & Reza Malekian & Zhixiong Li, 2019. "Time Series Analysis of Online Public Opinions in Colleges and Universities and its Sustainability," Sustainability, MDPI, vol. 11(13), pages 1-17, June.

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