基于BP神经网络预测某空气净化器环境电压的研究

Prediction of ambient voltage of an air purifier based on BP neural network

为实现某空气净化器环境电压的智能检测,运用sigmoid激活函数,构建了一种基于温升曲线预测环境电压的BP神经网络模型。结果显示,当输入层神经元数为27~53个,隐含层神经元数为25个时,对环境电压的预测能力较好。训练集的环境电压的实际值与预测值的相关系数为0.996,模型误差范围为-2.24%~5.26%,评估新数据的相对误差较小,具有良好的预测性,研究结果显示电压识别模型可用于智能预测环境电压。

In order to achieve intelligent detection of the ambient voltage of an air purifier,a BP neural network model based on the temperature rise curve to predict the ambient voltage is constructed by using the sigmoid activation function.The results showed that when there were 27~53 neurons in the input layer and 25 neurons in the implicit layer,the prediction ability of the ambient voltage was better.The correlation coefficient between the actual value of the environmental voltage and the predicted value of the training set is 0.996,the model error range is-2.24%~5.26%,the relative error of the evaluation of the new data is small,and it has good predictability,and the results show that the voltage identification model can be used to intelligently predict the ambient voltage.