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针对网络舆情发展过程的复杂性和多成分的特点,本文提出一种基于小波分析和人工神经网络的网络舆情建模和预测方法。利用小波变换将舆情发展过程分解到不同的尺度层面上,形成舆情发展过程的整体趋势、细节等部分,然后通过人工神经网络对每个部分进行建模并最终达到预测的目的,并与其他预测模型进行对比实验。结果表明,相对于其他模型,本文提出的小波-人工神经网络预测模型具有较高的精确度和稳定性。
In view of the complexity and multicomponent characteristics of the network public opinion development process, this paper presents a method of network public opinion modeling and prediction based on wavelet analysis and artificial neural network. The process of public opinions development is decomposed into different scales by using wavelet transform to form the overall trends and details of the public opinion development process. Then, each part is modeled by artificial neural network and finally predicted. Model for comparative experiments. The results show that compared with other models, the wavelet-artificial neural network prediction model proposed in this paper has higher accuracy and stability.