Multi Points Updated and Distance Filtered Kriging Surrogate Model： Application in EOSS Optimization  

作　　者：LIU Xiaolu CHEN Yingwu CHEN Yingguo HE Renjie 

机构地区：[1]School of Information System and Management, National University of Defense Technology, Changsha 410073, China

出　　处：《Chinese Journal of Electronics》2013年第1期209-213,共5页电子学报（英文版）

基　　金：This work is supported by the National Natural Science Foundation of China （No.70171156, No.70971131）.

摘　　要：We put forward a multi points updated and distance filtered Kriging surrogate model. When building Kriging models, two update approaches are used to select infilling points： optimal points and maximized expected improvement. We use Improved general pattern search （IGPS） algorithm to get these points. In IGPS, search step is substituted by GA and SQP and poll step is retained. To decrease simulation times, we adopt a distance filter to eliminate potentially replicated samples. A satellite or-bit parameter optimization problem is formulated, which is solved by the proposed method and STK/Analyzer re- spectively. The results showed that Kriging models, which use multi update points and distance filter, yield global approximations that are more accurate than Analyzer.

关 键 词：Kriging surrogate model Maximizedexpected improvement Distance filter Improved generalpattern search （IGPS） EOSS （Earth observation satellitesystem） optimization. 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] S159.2[自动化与计算机技术—计算机科学与技术]