Titlebook: Handbook of Dynamic Data Driven Applications Systems; Volume 1 Erik P. Blasch,Frederica Darema,Alex J. Aved Book 2022Latest edition This is

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https://doi.org/10.1007/978-3-663-20264-6e utility of the proposed algorithms.The proposed framework results in a estimates of the surface shape of the target object, which can subsequently used in forward models for prediction, data assimilation and subsequent sensor tasking operations. Sensitivity analysis is used to quantify the uncerta

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https://doi.org/10.1007/978-3-642-82733-4e the belief on the trajectory of the target, and the searcher actively steers the measurement process to improve its knowledge about the location of the target. In particular, we make two main contributions. The first regards the target trajectory estimation. We show how to perform optimal Bayesian

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https://doi.org/10.1007/978-3-030-74568-4DDDAS; Controls; Instrumentation; Big Data; High performance computing; Cyber physical systems; UAVs; data

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978-3-030-74570-7This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright pro

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Introduction to the Dynamic Data Driven Applications Systems (DDDAS) Paradigm,nal physical and other analysis models and methods, run-time measurements, and computational architectures. Some of the foremost early applications of DDDAS successes range from environmental assessment of adverse weather and natural disasters such as tornadic activity, hurricane formation and traje

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