This paper predicts library reader flow mainly based on BP neural network.In this paper,BP nerve network model is established.The data is input from the input layer and transferred in transfer layer.Then we can get relative error by comparing the prediction data from output layer to the actual value,and constantly adjust the weights of the networks and the threshold value to obtain the minimum error.Matlab is used to analyze the data and prediction results.The simulation results show that BP neural network is a effective method to predict library reader flow.%本文主要基于BP神经网络对图书馆读者流量进行预测,建立BP神经网络模型,从输入层输入数据,逐层传递,将输出层输出的预测值与实际值比较得出相对误差,并以此为根据不断调整网络的权值和阈值,以获得最小误差。利用Matlab仿真模型对数据及预测结果误差进行分析,结果表明BP神经网络对图书馆读者流量进行预测具有较好的效果。
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