新冠肺炎疫情极限IR实时预测模型

Extreme IR Model for COVID -19 Real-Time Forecasting

  • 摘要: 针对现有模型在开放空间的预测和时变参数估计上存在的局限性,该文在已知病毒传播规律的基础上,将极限学习机与动力学模型结合,提出了一种新的极限IR预测模型。通过对SIR模型的改进,该模型将病毒传播过程简化为感染态、治愈态和死亡态,并对时变函数及疫情趋势进行预测,解决了疫情中现有确诊人数、死亡人数和治愈人数实时预测的难题。实验证明,极限IR算法可准确实现疫情趋势的实时预测,为新型冠状肺炎疫情发展趋势提供了一种有效的数据分析模型。

     

    Abstract: The coronavirus diseases around the end of 2019 (COVID-19) has spreading within open space and the parameters of this dynamic system are time variant. As consequences, existed models are impractical for real-time forecasting of the COVID-19 trend. Therefore, this study provides a real-time trend forecasting model called extreme IR model with the propagation law. Based on SIR model, the propagation of COVID-19 is simplified to three states. Also, the model uses extreme learning machine to generate the parameters of each state. As a result, the proposed model can evaluate time-variant parameter and predict the number of confirmed cases, dead cases and recovered cases during spreading process. The experiment demonstrates that the extreme IR model achieves accurate real-time prediction. Hence, this paper provides an effective approach to analyze the trend of the diseases.

     

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