Static and dynamic neighbor interaction of flocking model in Newtonian approach

There is some collective motion that does by animal groups, such as bird flocks, fish school, insect swarms. In nature, Structural order showed movement and direction every single individual makes them safer and more efficient. The desire to flock is dependent on the nearest-neighbor distance, even though there are other parameters that can affect flocking. To get more insight into this system, we manipulate interaction with each particle in two situations. In a static condition, we set each particle to interact with their group only, which means the particle will not respond to other entities that not selected. In a dynamic situation, we set each particle can interact with a predator as long as the neighbor is in the orientation and attraction zones of the particle. The Newtonian approach used to handle physical parameters such as position, velocity, and, acceleration of the particles, then these physical parameters are calculated and updated by the Euler integration. Some patterns appear in our simulation, such as line formation and dynamic parallel group.