Abstract:

In order to effectively utilize the practical records of firefighting and rescue teams and extract successful experiences from emergency rescue cases, an analysis model was constructed by combining the TF-IDF algorithm and VOSviewer literature visualization analysis technology. The model aimed to analyze the common patterns and characteristics of success and failure in emergency rescue cases, and summarize the current status and development trends of emergency rescue in China. The database for this model consisted of 185 typical emergency rescue cases from the years 2007 to 2019, categorized based on types of emergency rescue actions, namely natural disasters, traffic accidents, building collapses, hazardous chemical leaks and firefighting. The results indicate that the influencing factors of emergency rescue actions in China mainly manifest in four aspects: people (rescue teams), machine (equipment technology), environment and management. Environmental factors generally have a negative impact, while the other three factors exhibit both positive and negative influences. Furthermore, there are differences in the leading influencing factors of different types of emergency rescue actions. "Machine" factors stand out in natural disasters. "Management" factors are prominent in traffic accident. "Machine" and "environment" factors are emphasized in building collapses. Hazardous chemical leaks pose outstanding issues in all four aspects of "people, machine, environment and management". "Machine" factors are highlighted in firefighting rescue.

Key words: term frequency-inverse document frequency (TF-IDF), VOSviewer, emergency rescue, fire rescue, visual analysis, case analysis