A simulation research on casualty prediction based on system dynamics and agent-based modeling
10.16781/j.0258-879x.2018.05.0510
- Author:
Bo PENG
1
Author Information
1. Institute of Health Service and Transfusion Medicine, Academy of Military Medical Sciences, Academy of Military Sciences PLA China
- Publication Type:Journal Article
- Keywords:
Casualty generation;
Casualty prediction;
Multi-agent;
System dynamics
- From:
Academic Journal of Second Military Medical University
2018;39(5):510-514
- CountryChina
- Language:Chinese
-
Abstract:
Objective To simulate, predict and analyze the total number, spatial and temporal distribution, and proportion and composition distribution of combat casualties. Methods System dynamics was used to construct an combat process simulation and casualty prediction model. Agent-based modeling was used to import macro casualty data from the prediction model, split the casualty data and assign the combat injury information in a specific proportion. Results The casualty prediction model based on system dynamics could integrate with specific operational mission and analyze the combat influencing factors, weapon destruction performance, and level of protection in both Red and Blue sides. The casual-effect loop and the stock-flow model were constructed on combat process. The degree of damage to the target of the two sides in the battle was transformed to casualty data. We extracted the macro casualty data from the combat casualty prediction model. Through constructing the corresponding relationship between the destruction degree of operational objectives and war wound information of all kinds, we assigned and simulated the traumatic condition of each individual casualty and completed the conversion from casualty to wounded flow. Conclusion Constructed casualty prediction model based on system dynamics and the casualty generating model based on agent can scientifically calculate the spatial, temporal distribution and proportion and composition of casualties.
