Research on dynamic risk early warning model for chemical processes based on artificial intelligence
基于人工智能的化工过程动态风险预警模型研究

摘要

化工过程中的风险预警一直是工业安全管理的重要课题。随着人工智能技术的快速发展，传统的风险评估方法逐渐暴露出效率低、准确性差的问题。本研究提出了一种基于人工智能的化工过程动态风险预警模型，通过结合机器学习和数据挖掘技术，实时监控化工过程中的异常行为，提前预测潜在风险。该模型能够有效提高风险预警的准确性和响应速度，减少人为因素干扰，提升安全管理水平。实验结果表明，人工智能模型在多个化工场景中具有较高的预测精度，能够为安全决策提供有效支持。

Abstract

Risk early warning in chemical processes has always been an important topic in industrial safety management. With the rapid development of artificial intelligence technology, traditional risk assessment methods have gradually exposed problems such as low efficiency and poor accuracy. This study proposes a dynamic risk early warning model for chemical processes based on artificial intelligence. By integrating machine learning and data mining technologies, the model monitors abnormal behaviors in chemical processes in real time and predicts potential risks in advance. It can effectively improve the accuracy and response speed of risk early warning, reduce the interference of human factors, and enhance the level of safety management. Experimental results show that the artificial intelligence model has high prediction accuracy in multiple chemical scenarios and can provide effective support for safety decision-making.