基于一维卷积神经网络的工业产业安全评价与预警研究

文章基于产业安全理论和相关文献研究，建立了工业产业安全评价指标体系，运用熵权—灰色关联分析法评价2000—2018年工业产业安全状况，再构建LSTM神经网络预测模型预测2019—2023年工业产业安全各评价指标数据，将所有预测数据和历史数据相结合，建立基于一维卷积神经网络的工业产业安全预警模型，并对2019—2023年工业产业安全状况进行系统预警。结果表明:随着工业改革不断深入，安全度增速上升；预测未来五年工业产业安全程度整体处于安全状态。

Research on Industry Security Evaluation and Early Warning Based on One-dimensional Convolutional Neural Network

Based on industrial safety theory and related literature research, this paper establishes an industrial safety evaluation index system, uses entropy Weight-Grey correlation analysis to evaluate industrial safety from 2000 to 2018, and builds an LSTM neural network prediction model to predict the data of various evaluation indicators of industrial safety from 2019 to 2023. It combines all prediction data with historical data to establish an early warning model of industrial safety based on one-dimensional convolutional neural network, and to provide a systematic early warning on the industrial safety situation from 2019 to 2023. The results show that with the continuous industrial reforms, the safety rate has kept growing; so it predicts that the overall safety of industry in the next five years will be secure.