基于深度学习的多维情景空间下群体性事件分析与预测研究

doi:10.16381/j.cnki.issn1003-207x.2020.08.015

Abstract

Abstract: The increasing mass incidents have greatly affected the harmony and stability of the society in the context of social transformation. A multi-dimensional scenario space model is constructed by using the "Scenario-Sub-Scenario-Object-Factor" model to decompose of all kinds of mass incidents and extract related influential factors. Based on multi-dimensional scenario space model, the convolutional neural network model is applied to mass incidents prediction, its principle is explained in detail and practical applications are discussed. A data set, formed by encoding a group of mass incidents' cases based on the multidimensional scenario space model is used to train (test) the predictive model and evaluat its validity via Area Under Curve (AUC). Furthermore, the effect of different factors on the prediction of mass incidents is analyzed and the direction of emergency management is indicated.

Key words: mass incidents, multi-dimensional scenario space model, convolutional neural network, prediction, emergency management

CLC Number:

C931

ZHANG Ding-hua, LI Wei-jun, LI Cheng, SHEN Shi-fei. The Researchon the Analysis and Prediction of Mass Incidentsin Multi-dimensional Scenario Space Based on Deep Learning[J]. Chinese Journal of Management Science, 2020, 28(8): 172-180.

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The Researchon the Analysis and Prediction of Mass Incidentsin Multi-dimensional Scenario Space Based on Deep Learning

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