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传染病预测是卫生工作中的一项重要工作,神经网络作为一种相对成熟的机器学习方法,能否较好地应用于传染病预测模型的构建中,值得进一步探讨。本文介绍了反馈神经网络的基本原理和模型设计,并通过既往研究实例说明了神经网络模型在传染病预测中的应用。神经网络具有信息存储方式独特、容错性良好以及自适应能力强大等优点,可以识别变量间复杂的非线性关系,探讨其在传染病预测中的应用途径和方法具有重要意义和广阔前景。
Prediction of infectious diseases is an important work in health work. As a relatively mature machine learning method, neural network can be well applied to the construction of infectious disease prediction model, which deserves further exploration. This paper introduces the basic principle and model design of feedback neural network, and illustrates the application of neural network model in the prediction of infectious diseases through the previous research examples. Neural network has the advantages of unique information storage, good fault tolerance and strong adaptability. It can identify the complex nonlinear relationship between variables and explore its application approaches and methods in the prediction of infectious diseases is of great significance and broad prospects.