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What is In Situ Adaptive Tabulation mean?
In situ adaptive tabulation (ISAT) is an algorithm for the approximation of nonlinear relationships. ISAT is based on multiple linear regressions that are dynamically added as additional information is discovered. The technique is adaptive as it adds new linear regressions dynamically to a store of possible retrieval points. ISAT maintains error control by defining finer granularity in regions of increased nonlinearity. A binary tree search transverses cutting hyper-planes to locate a local linear approximation. ISAT is an alternative to artificial neural networks that is receiving increased attention for desirable characteristics, namely:
scales quadratically with increased dimensionapproximates functions with discontinuitiesmaintains explicit bounds on approximation errorcontrols local derivatives of the approximating functiondelivers new data training without re-optimizationISAT was first proposed by Stephen B. Pope for computational reduction of turbulent combustion simulation and later extended to model predictive control. It has been generalized to an ISAT framework that operates based on any input and output data regardless of the application. An improved version of the algorithm was proposed just over a decade later of the original publication, including new features that allow you to improve the efficiency of the search for tabulated data, as well as error control.
referencePosted on 06 Jan 2025, this text provides information on Miscellaneous in General related to General. Please note that while accuracy is prioritized, the data presented might not be entirely correct or up-to-date. This information is offered for general knowledge and informational purposes only, and should not be considered as a substitute for professional advice.
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