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Simulated annealing is an optimization technique that takes geospatial data as input (e.g. realization) and iteratively modifies it using neighborhoods to optimize an objective function (e.g. difference between theoretical and empirical variogram). This issue consists of designing and implementing a general Annealing transform following our TransformsBase.jl API that takes arbitrary objective functions as input to be applied to neighborhoods of the data.
The text was updated successfully, but these errors were encountered:
Simulated annealing is an optimization technique that takes geospatial data as input (e.g. realization) and iteratively modifies it using neighborhoods to optimize an objective function (e.g. difference between theoretical and empirical variogram). This issue consists of designing and implementing a general Annealing transform following our TransformsBase.jl API that takes arbitrary objective functions as input to be applied to neighborhoods of the data.
The text was updated successfully, but these errors were encountered: