Abstract
BackgroundThe article proposes a network public opinion risk assessment model for earthquake disasters, which can provide an effective support for emergency departments of China.MethodIt 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.ResultsThe 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.ConclusionThe risk assessment method of network public opinion can be used in the practice of earthquake disaster decision.
Highlights
By June 2018, the number of China’s internet population reached 802 million, and internet popularity is up to 54.3%
The risk evaluation system of earthquake network public opinion is established that is an essential task for improving the efficiency and capacity of emergency response
This study leads to the following conclusions, (1) This article put forward the risk monitoring indexes for earthquake network public opinion
Summary
The article proposes a network public opinion risk assessment model for earthquake disasters, which can provide an effective support for emergency departments of China. Data Availability Statement: All data necessary to replicate the reported study findings are within the paper. Full data sets are available from network collection: http://www.chinasafety.gov.cn/, and other some data came from: http://www.gsdata.cn/.
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