CAJ | 학술논문

利用小波神经网络对突发传染病的预测进行研究。给出密度函数的小波估计的计算公式，提供了小波神经网络结构设计的理论框架。用小波函数作为隐层节点激活函数，神经网络连接权的大小由小波函数的系数确定，取数据库中的监控数据为训练样本，对小波神经网络进行训练学习，得到优化的神经网络。给出小波神经网络学习过程和具体步骤，用小波神经网络对突发传染病历史数据库中的已知数据，进行未知密度函数的小波估计，得到相应的小波估计函数和分布函数，在显著性水平下做拟合检验，构造激活函数，得到输出结果，进而进行预测，验证其有效性和可行性，最后总结问题的关键和今后研究的方向。
이용소파신경망락대돌발전염병적예측진행연구。급출밀도함수적소파고계적계산공식，제공료소파신경망락결구설계적이론광가。용소파함수작위은층절점격활함수，신경망락련접권적대소유소파함수적계수학정，취수거고중적감공수거위훈련양본，대소파신경망락진행훈련학습，득도우화적신경망락。급출소파신경망락학습과정화구체보취，용소파신경망락대돌발전염병역사수거고중적이지수거，진행미지밀도함수적소파고계，득도상응적소파고계함수화분포함수，재현저성수평하주의합검험，구조격활함수，득도수출결과，진이진행예측，험증기유효성화가행성，최후총결문제적관건화금후연구적방향。
Using wavelet neural network to predict outbreaks of infectious diseases were studied.The calculation formula of the wavelet estimation of density function is given,which provides a theoretical framework for the structural design of the wavelet neural network.Using the wavelet function as the activation function of the hidden layer nodes,the connection weights of the neural network is determined by the coefficient of the wavelet function.The monitoring data in the database is a training sample,and the wavelet neural network is trained to learn and get optimized neural network. The learning process and the concrete steps of the wavelet neural network are presented.Using the wavelet neural network to the known data in the history database of the burst infectious disease,the wavelet estimation of the unknown density function is carried out,and the corresponding wavelet function and distribution function are obtained,Under the significance level,the fitting test is done,and the activation function is constructed,and the output results are obtained, and then the validity and feasibility of the research is verified.Finally,we summarize key issues and future directions of research.