Nguyen Linh Thi Hoai, Tạ Việt Tôn, Yagi Atsushi
Department of Information and Physical Sciences, Graduate School of Information Science and Technology, Osaka University, Suita, Osaka 565-0871, Japan.
Promotive Center for International Education and Research of Agriculture, Faculty of Agriculture, Kyushu University, Nishi-ku, Fukuoka 812-8581, Japan.
J Theor Biol. 2016 Oct 7;406:116-23. doi: 10.1016/j.jtbi.2016.07.017. Epub 2016 Jul 22.
This paper is devoted to studying obstacle avoiding patterns and cohesiveness of fish school. First, we introduce a model of stochastic differential equations (SDEs) for describing the process of fish school's obstacle avoidance. Second, on the basis of the model we find obstacle avoiding patterns. Our observations show that there are clear four obstacle avoiding patterns, namely, Rebound, Pullback, Pass and Reunion, and Separation. Furthermore, the emerging patterns change when parameters change. Finally, we present a scientific definition for fish school's cohesiveness that will be an internal property characterizing the strength of fish schooling. There are then evidences that the school cohesiveness can be measured through obstacle avoiding patterns.
本文致力于研究鱼群的避障模式和内聚性。首先,我们引入一个随机微分方程(SDEs)模型来描述鱼群的避障过程。其次,基于该模型我们找出了避障模式。我们的观察表明,存在四种明显的避障模式,即反弹、回撤、通过和重聚以及分离。此外,当参数变化时,出现的模式也会改变。最后,我们给出了鱼群内聚性的科学定义,它将是表征鱼群聚集强度的一种内在属性。进而有证据表明,鱼群内聚性可以通过避障模式来衡量。