基于多层感知器的某矿职工呼吸系统的识别预测

MLP - based Employees of A Mine Identification of The Respiratory System Forecast

笔者利用基于多层感知器的神经网络,在描述性分析的基础上,建立了某矿职工呼吸系统的神经网络识别预测模型,并分析预测效果。实验表明:该多层感知器的神经网络预测模型的拟合能力强,能较好地识别预测出呼吸道患者。但由于数据来源单一,导致该模型无法推广到其他矿区。

In this paper, MLP -based neural network, the descriptive analysis, a mine worker identification of respiratory neural network prediction model was built, and results were analyzed the forecast. Experiments showed that the multiply - layer perception neural network prediction model was fit and strong, and it could better identify the predicted respiratory patients. However, due to a single source of data, the model could not be extended to other mines.