基于状态向量的危化品事故分析方法及应用

危险化学品行业属于高危险性行业，各类爆炸、火灾、泄漏和中毒事故时有发生.传统的基于因果关系的事故链分析方法受限于传统安全工程所依赖的技术基础和假定无法适应于今天所建造的复杂系统.本文以事故致因理论为基础，分析危化品事故形成的主要影响因素，构建了危化品事故状态向量，全面描述导致危化品事故发生的因素，并基于构建的状态向量进行危化品事故分析预测应用.利用高维向量对事故状态进行了定义，尽最大可能考虑了造成事故发生的众多因素，并利用支持向量机学习算法，建立事故预测模型.对已掌握的危化品事故进行的样本实验表明，本文提出的危化品事故预测方法，可有效快速的甄别事故状态，对危化品行业事故的预测预防具有积极意义.

Analysis Method and Application of Hazardous Chemical Accidents Based on State Vector

Hazardous chemicals industry is a high risk industry. Explosion, fire, leakage, and poisoning accidents occur frequently. Traditional causality-based accident chain analysis method is limited by the technical basis and assumptions that traditional safety engineering relies on, and cannot adapt to today''s complex systems. Based on the accident causation theory, this study analyses the main factors affecting the formation of dangerous chemicals accidents, constructs a state vector of dangerous chemicals accidents, describes the factors leading to dangerous chemicals accidents comprehensively, and uses the state vector to analyze and forecast dangerous chemicals accidents. The high dimension vector is used to define the accident state, and the most possible factors are considered. Using support vector machine learning algorithm, an accident prediction model is established by accident state vector. A sample test of the hazardous chemical accident shows that the method can differentiate accident state accurately and efficiently, and demonstrate a positive significance on accident prediction of hazardous chemicals.