Abstract: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.