Emergency Response Plan for Spontaneous Combustion Based on Case-Based Reasoning

In order to avoid missing the best opportunity for emergency rescue in the event of spontaneous combustion and to prevent accidents from developing further, this paper proposed a method to generate an emergency response plan for spontaneous combustion based on case-based reasoning (CBR). Firstly, we adopted Hadoop big data retrieval technology to establish a case library for spontaneous combustion; then, our team applied CBR technology and introduced the differential determination symbol to calculate case similarity; furthermore, we quickly generated an emergency response plan for spontaneous combustion with the help of the Python program; and finally, we used a case to verify the effectiveness of the method. Overall, the results showed that the emergency response plan generated using this proposed method was consistent with the actual situation of the accident case and, compared with other relevant representative algorithms, the results in this paper were more accurate. In practice, this method may be helpful in providing support for generating emergency response plans for spontaneous combustion.

Automated summary

This paper presents a method for generating an emergency response plan for spontaneous combustion based on case-based reasoning. By establishing a case library, applying CBR technology, and utilizing a Python program, an emergency response plan for spontaneous combustion can be quickly generated. The results show that the proposed method is consistent with the actual situation and more accurate compared to other algorithms, providing support for emergency response plan generation in spontaneous combustion incidents.