A complex system is a setup where many simple parts interact, creating certain overall effects. Examples of complex systems around us include weather patterns, economic functions, group movements of insects or birds, and the Internet's structure. Modeling these systems enables us understanding realistic phenomena and building detailed simulations. It is hard to directly model the entire system, but on the other hand, modeling individual components does not represent the behavior of the entire system. In this paper, we modeled the entire complex system by decomposing it into components and installing methods which resolved nature of each component. In the experiment, we modeled dynamics of insect group behavior. Considering invariances of the system, we proposed a method involves two tricks which were effective for precisely modeling the system which resulted in performing high accuracy.