Dynamic Data Assimilation - Beating the Uncertainties
Dinesh G. Harkut
Abstract
Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.
Topics & Concepts
Data assimilationKalman filterComputer scienceAssimilation (phonology)Artificial neural networkArtificial intelligenceProcess (computing)Machine learningMeteorologyGeographyLinguisticsOperating systemPhilosophyMeteorological Phenomena and Simulations