Application of the Cross-Entropy Method to Dual Lagrange Support Vector Machine

2009 ◽  
pp. 595-602 ◽  
Author(s):  
Budi Santosa
Keyword(s):  
Support Vector Machine ◽  
Entropy Method ◽  
Cross Entropy ◽  
Support Vector ◽  
Cross Entropy Method ◽  
The Cross

scholarly journals Improved Cross Entropy Support Vector Machine Method for Structural Design Optimization

2018 ◽  
Vol 36 (3) ◽  
pp. 448-455
Author(s):  
Hang Zhang ◽  
Hongshuang Li
Keyword(s):  
Support Vector Machine ◽  
Design Optimization ◽  
Voronoi Tessellation ◽  
Entropy Method ◽  
Cross Entropy ◽  
Support Vector ◽  
Local Optimum ◽  
Machine Method ◽  
Cross Entropy Method ◽  
Structural Design Optimization

Aiming at the difficulties of implicit functions and high computation cost in engineering design optimization, a combined method is proposed in this paper, which takes advantage of support vector machine(SVM) and cross entropy method(CE). Used the ’Latinized’ centroidal Voronoi tessellation(LCVT) which can generate much uniform supporting points in the design variable space, a high accurate surrogate model is obtained by SVM. At the same time, the traditional cross entropy method is improved by the concepts of "global elite samples" and the "local elites samples" and a new parameter updating strategy for extracting the useful information in iteration history. To avoid trapping in the local optimum, a mutation operation is also included in the proposed method. Two numerical examples are used to illustrate the performance of the improved method superior to that of the traditional one. Finally, an engineering example is employed to demonstrate the feasibility of the proposed method in the field of engineering.

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