Numerical Modeling of the Collective Motion of Fish Schools using Cellular Automaton
【摘要】：Schooling of fish is one of the most common collective motions in nature. In the past decades, collective motions have been studied extensively based on various theories. In this work, the principle of least potential energy is incorporated into a cellular automaton algorithm to simulate the motion of fish schools. In the present model, it is assumed that the potential energy of a fish school consists of two parts, viz. Part-I induced by distance and Part-II determined by orientation. By minimizing the potential energy, several typical patterns of fish schooling can be obtained in the evolution process of cellular automaton. The rationality of the proposed method is verified by the comparison between the numerical modeling and the observation on red zebrafish.