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A kriging-based optimization approach is proposed for problems with large data sets and high dimensionality. Memory usage is maintained via model centering aided by minimizing the impact of information loss… Click to show full abstract
A kriging-based optimization approach is proposed for problems with large data sets and high dimensionality. Memory usage is maintained via model centering aided by minimizing the impact of information loss on accuracy of new point prediction using points aggregation techniques. The eight-parameter TEAM problem 22 is revisited in the context of computational efficiency and accuracy.
Keywords:
data sets;
optimization approach;
based optimization;
large data;
points aggregation;
kriging based
Journal Title: IEEE Transactions on Magnetics
Year Published: 2017
Link to full text (if available)
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Journal Title: IEEE Transactions on Magnetics
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!