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VISUALISING SPECIATION IN MODELS OF CICHLID FISH

机译:鱼鳞模型中的可视化规格

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An Agent-Based model of speciation in cichlid fish has been implemented. When run, this generates large amounts of trace data in which speciation is an implicit, near unobservable, processes. Fuzzy C-Means Clustering is used to identify species extant at the end of simulation, and the power set of these species is the potential set of ancestral species. Membership values for all fish in each of these theoretical ancestral species are calculated, and total set membership for each of these species is plotted against time. The resulting graph is to be a clear visualisation of the process of speciation, and the appearance and disappearance of intermediate species. Our approach allows the visualisation of speciation resulting in larger numbers of final species than was possible using previous techniques based on measuring correlations between explicit properties of modeled organisms, and is also unaffected by changes to the properties used to model fish.
机译:已实施了丽鱼科鱼类基于物种的物种形成模型。运行时,这会生成大量的跟踪数据,在这些数据中,形态是一个隐式,几乎不可观察的过程。模糊C均值聚类用于识别仿真结束时存在的物种,这些物种的能力集就是潜在的祖先物种集。计算这些理论祖先物种中所有鱼类的隶属度值,并针对时间绘制每种鱼类的总集合隶属度。生成的图形将清晰地显示物种形成过程以及中间物种的出现和消失。我们的方法允许可视化的物种形成,从而导致最终物种的数量比使用以前的技术(基于对建模生物的显性特性之间的相关性的测量)所使用的最终物种数量更大,并且不受用于建模鱼的特性变化的影响。

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