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Stochastic modeling of particle movement with application to marine biology and oceanography

机译:粒子运动的随机建模及其在海洋生物学和海洋学中的应用

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摘要

We consider some stochastic models that have been proposed for the trajectories of moving objects, including Brownian motion. This leads to the development of a general approach for dealing with paths including the use of functional stochastic differential equations. We then present an empirical example based on the surface drifting movements of a small satellite-linked radio transmitter tag after it detached from a whale shark in the western Indian Ocean. The daily estimates of the tag's locations were determined from transmissions received at irregular times by polar-orbiting satellites of the Argos Data Collection and Location Service system.An aspect of the empirical analysis is a study of how well the sea surface currents that are derived from remote sensing and sea surface models compare to the movements of the drifting tag. A second is to develop a predictive model using the past tag locations, the currents and the winds.
机译:我们考虑了一些针对运动对象(包括布朗运动)的轨迹提出的随机模型。这导致了一种用于处理路径的通用方法的发展,其中包括使用函数随机微分方程。然后,我们根据一个小型的与卫星相关的无线电发射机标签从印度洋西部的鲸鲨脱离后的表面漂移运动,提出一个经验示例。标签位置的每日估计值是由Argos数据收集和位置服务系统的极轨卫星在不规则时间接收到的传输中确定的。实证分析的一个方面是研究从中获得的海面流状况如何遥感和海面模型与漂移标签的运动进行了比较。第二个是使用过去的标签位置,潮流和风来建立预测模型。

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