基于案例推理的化工园区应急资源需求预测

为确定化工园区突发事故的应急资源需求,提出了一种基于案例推理的化工园区应急资源需求预测方法。该方法主要由三部分组成:(1)基于案例推理的模型构建;(2)化工园区事故的案例描述;(3)基于人工神经网络的案例适应。最后,以石化园区火灾爆炸事故的应急资源需求预测验证该方法的有效性。研究表明,该方法可以实时地对化工园区应急资源需求进行预测,为化工园区的应急资源储备和配置提供支持。

Emergency resources demand prediction in chemical industry park based on case-based reasoning

In order to determine the emergency resources demand of the chemical industry park, a case-based reasoning (CBR) method for the emergency resources demand prediction of the chemical industry park was proposed. The method consists of three parts: (1) Model construction based on case-based reasoning; (2) Case representation of the accident that occurs in the chemical industry park; (3) Case adaptation based on the artificial neural network. Finally, the validity of this method is verified by the prediction of emergency resources demand for fire and explosion accidents in petrochemical parks. The research shows that the proposed method can predict the emergency resource demand of chemical industry park in real time, and provide support for the emergency resource reserve and allocation of chemical industry park.