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Analysis of juvenile tuna movements as correlated random walk

机译：作为相关随机游走的金枪鱼幼鱼运动的分析

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We explore how a stochastic model provides the most promising avenue towards predicting fish movement. To construct a stochastic model describing fish movement, trajectories of ten juveniles in a water tank were analyzed from a stochastic point of view. The heading angle was defined as a random variable. Our analysis found that the most probable forward heading angle was between 0° and 22.5° (probability ~78%), followed by angles between 22.5° and 45° (probability ~10%). We also found that the choice of future heading angle depends on the current heading angle. Therefore, we treated heading angle state as a first-order Markov process and constructed a correlated random walk model describing juvenile movement in a water tank. Our stochastic model simulated a trajectory similar to observed trajectories. We used the model as a tool for estimating the probability distribution of potential fish path outcomes. We derived the distribution of potential outcomes from a large number of simulations (N = 1000) and investigated these trajectories. We collected a set of juvenile trajectories that collided with the tank and estimated the probability of juvenile collisions with the tank.
机译：我们探索随机模型如何为预测鱼类运动提供最有希望的途径。为了构建描述鱼类运动的随机模型，从随机的角度分析了水箱中十个少年的轨迹。航向角定义为随机变量。我们的分析发现，最可能的向前航向角在0°和22.5°之间（概率约为78％），其次是在22.5°和45°之间的角度（概率约为10％）。我们还发现，未来航向角的选择取决于当前航向角。因此，我们将航向角状态视为一阶马尔可夫过程，并构建了描述水箱中青少年运动的相关随机游走模型。我们的随机模型模拟的轨迹类似于观察到的轨迹。我们将模型用作估计潜在鱼径结果概率分布的工具。我们从大量模拟（N = 1000）中得出了潜在结果的分布，并研究了这些轨迹。我们收集了一组与坦克相撞的少年轨迹，并估计了少年与坦克相撞的可能性。

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