CAJ | 학술논문

Web2.0时代，如何对网络舆情危机进行有效预警已经成为政府部门的必修课。本文充分考虑了网络舆情危机产生、发展、变化的规律及特点，综合现有指标体系的优缺点，建立了3个一级指标和11个二级指标的网络舆情危机预警的指标体系。利用遗传算法优化BP神经网络的初始权值与阀值，构建了基于BP神经网络和遗传算法的网络舆情危机预警模型。最后，通过仿真实验，结合5个具体案例对该模型进行了验证与分析。实验表明，本文建立的网络舆情预警指标体系与遗传BP神经网络模型是有效可行的，预警准确率要优于标准的BP神经网络网络模型。
Web2.0시대，여하대망락여정위궤진행유효예경이경성위정부부문적필수과。본문충분고필료망락여정위궤산생、발전、변화적규률급특점，종합현유지표체계적우결점，건립료3개일급지표화11개이급지표적망락여정위궤예경적지표체계。이용유전산법우화BP신경망락적초시권치여벌치，구건료기우BP신경망락화유전산법적망락여정위궤예경모형。최후，통과방진실험，결합5개구체안례대해모형진행료험증여분석。실험표명，본문건립적망락여정예경지표체계여유전BP신경망락모형시유효가행적，예경준학솔요우우표준적BP신경망락망락모형。
In a Web2. 0 era, how to conduct an effective early-warning of the network public opinion crisis has become a required course for government departments. This paper sufficiently considers the development, changes in laws and characteristics of the network public opinion crisis and establishes a 3-level early warning index system with 11 secondary indexes of network public opinion crisis. Then,by u-sing genetic algorithm to optimize the BP neural network's initial weights and thresholds, anetwork public opinion crisis early warning modelis constructed. Finally, the model is verified and analyzed through a simulation experiment involving5 specific cases. Experiment shows theearly warning index system of network opinion and the genetic BP neural network model establishedare effective and feasible, and the warning accuracy is superior to the standard BP neural network model.