QQ客服 官方微博 反馈留言

	Two-level Multi-surrogate Assisted Optimization method for high dimensional nonlinear problems
	Li, Enying; Wang, Hu*; Ye, Fan
刊名	Applied Soft Computing Journal
	2016
卷号	46页码:26-36
关键词	AI Artificial Immune EICAM EI criterion assisted modeling EGO Efficient Global Optimization EI Expected Improvement GA Genetic Algorithm GMDH Group Method of Data Handling GSS Golden Section Sampling HDMR High Dimensional Model Representation LOOCV Leave-One-Out Cross Validation MAS Multi-surrogate Assisted Sampling algorithm EImax maximum EI MLS Moving Least Square NTS Number of Test Samples PR Polynomial Regression PSO Particle Swarm Optimization RAAE Relative Average Absolute Error RBF Radial Basis Function RMAE Relative Maximum Absolute Error SA Simulated Annealing STD Standard Deviation SAEO Surrogate Assisted Evolutionary Optimization SAO Surrogate Assisted Optimization SVR Support Vector Regression TMAO Two-level Multi-surrogate Assisted Optimization TLBO Teaching Learning-Based Optimization SAO HDMR Separable GMDH Multi-surrogate
ISSN号	1568-4946
DOI	10.1016/j.asoc.2016.04.035
URL标识	查看原文
WOS记录号	WOS:000377999900003;EI:20161902366707
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/5726751
专题	中南林业科技大学
作者单位	[Li, Enying] Cent South Univ Forestry & Teleol, Sch Logist, Changsha 41004, Hunan, Peoples R China.
推荐引用方式 GB/T 7714	Li, Enying,Wang, Hu*,Ye, Fan. Two-level Multi-surrogate Assisted Optimization method for high dimensional nonlinear problems[J]. Applied Soft Computing Journal,2016,46:26-36.
APA	Li, Enying,Wang, Hu*,&Ye, Fan.(2016).Two-level Multi-surrogate Assisted Optimization method for high dimensional nonlinear problems.Applied Soft Computing Journal,46,26-36.
MLA	Li, Enying,et al."Two-level Multi-surrogate Assisted Optimization method for high dimensional nonlinear problems".Applied Soft Computing Journal 46(2016):26-36.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。