TY - GEN
T1 - Non-uniform mode-pursuing sampling method based on multivariate multimodal distribution model
AU - Su, Hua
AU - Gu, Liangxian
AU - Gong, Chunlin
PY - 2012
Y1 - 2012
N2 - A non-uniform distributing based mode-pursuing sampling method on black-box problem is proposed for the computation-intensive global optimization problem. The multivariate multimodal distribution model is established based on the expensive sample points of original optimization problem, which is controlled by the convergence principle of multiple correlation coefficient through variance of probability distribution. More design points are generated progressively around the current optimal regions and constitute the non-uniform discrete design space. Non-uniform sampling strategy changes the uniform distributing characteristic of design space, improves the utilization efficiency of design points and strengthens the distribution rationality of discrete design space. Analytical and numerical test results show that the improved method is more efficient and accurate than standard mode-pursuing sampling method and traditional algorithms, and has broad prospects for the expensive black-box problem.
AB - A non-uniform distributing based mode-pursuing sampling method on black-box problem is proposed for the computation-intensive global optimization problem. The multivariate multimodal distribution model is established based on the expensive sample points of original optimization problem, which is controlled by the convergence principle of multiple correlation coefficient through variance of probability distribution. More design points are generated progressively around the current optimal regions and constitute the non-uniform discrete design space. Non-uniform sampling strategy changes the uniform distributing characteristic of design space, improves the utilization efficiency of design points and strengthens the distribution rationality of discrete design space. Analytical and numerical test results show that the improved method is more efficient and accurate than standard mode-pursuing sampling method and traditional algorithms, and has broad prospects for the expensive black-box problem.
UR - http://www.scopus.com/inward/record.url?scp=84874619149&partnerID=8YFLogxK
U2 - 10.1109/ICACI.2012.6463175
DO - 10.1109/ICACI.2012.6463175
M3 - 会议稿件
AN - SCOPUS:84874619149
SN - 9781467317436
T3 - 2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012
SP - 309
EP - 313
BT - 2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012
T2 - 2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012
Y2 - 18 October 2012 through 20 October 2012
ER -