A Kriging-Based Optimization Approach for Large Data Sets Exploiting Points Aggregation Techniques

作者：Li Yinjiang^*; Xiao Song; Rotaru Mihai; Sykulski Jan K

来源：IEEE Transactions on Magnetics, 2017, 53(6): 7001704.

DOI：10.1109/TMAG.2017.2665703

• Clustering
• kriging
• large data sets
• surrogate optimization

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.

• 出版日期2017-6