Evaluation of fire rescue teams' capability in lithium battery fire suppression based on decision tree

With the rapid development of the lithium battery industry, the frequency and hazards of lithium battery-related fire incidents have been increasing annually, presenting new challenges for fire rescue operations. Traditional fire suppression capability evaluation methods fail to comprehensively reflect the actual operational competencies of firefighting forces in addressing lithium battery fires. To address this gap, this study establishes a capability assessment model for fire and rescue teams utilizing decision tree algorithms. Through classification modeling of 23 capability indicators for firefighting forces and data analysis using the C4.5 Algorithm, this study identifies weaknesses in team capabilities and proposes targeted improvement pathways.