A novel CACOR-SVR multi-objective optimization approach and its application in aerodynamic shape optimization of high-speed train | |
Zhang Y; Guo DL(郭迪龙); Sun ZX(孙振旭); Chen DW | |
发表期刊 | SOFT COMPUTING |
2019-07-01 | |
卷号 | 23期号:13页码:5035-5051 |
ISSN | 1432-7643 |
摘要 | A chaos ant colony optimization algorithm for continuous domain is proposed based on chaos optimization theory and ant colony optimization algorithm. The searching abilities of optimization algorithms with different coding methods are compared, and the results indicate that the proposed algorithm has better performance than genetic algorithm and particle swarm optimization algorithm. Based on the non-dominated sorting concept and niching method, a multi-objective chaos ant colony optimization algorithm is also constructed and numerical results show that the improved algorithm performs well at solving multi-objective optimization problems. An optimal support vector regression model based on radial basis kernel function is developed for the small sample size and nonlinear characteristics of streamlined head optimization. On the basis of the above work, a multi-objective optimization design for the aerodynamic head shape of high-speed train is developed using a modified vehicle modeling function parametric approach. The optimization results demonstrate that the new optimization design method has exceptional searching abilities and high prediction accuracy. After optimization, the aerodynamic drag of the simplified train with three carriages is reduced by 10.52% and the aerodynamic lift of the tail car is reduced by 35.70%. The optimization approach proposed in the present paper is simple yet efficient and sheds light on the engineering design of aerodynamic shape of high-speed trains. |
关键词 | Chaos ant colony optimization Support vector machine Multi-objective optimization Vehicle modeling function High-speed trains |
DOI | 10.1007/s00500-018-3172-3 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000469418900031 |
关键词[WOS] | ALGORITHMS |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications |
资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences (class B)[XDB22020000] ; National Key Research & Development Projects[2017YFB0202800] ; Computing Facility for Computational Mechanics Institute of Mechanics at the Chinese Academy of Sciences |
项目资助者 | Strategic Priority Research Program of the Chinese Academy of Sciences (class B) ; National Key Research & Development Projects ; Computing Facility for Computational Mechanics Institute of Mechanics at the Chinese Academy of Sciences |
论文分区 | 二类 |
力学所作者排名 | 1 |
RpAuthor | Yang, Guo Wei |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://dspace.imech.ac.cn/handle/311007/79325 |
专题 | 流固耦合系统力学重点实验室 |
通讯作者 | Sun ZX(孙振旭) |
推荐引用方式 GB/T 7714 | Zhang Y,Guo DL,Sun ZX,et al. A novel CACOR-SVR multi-objective optimization approach and its application in aerodynamic shape optimization of high-speed train[J]. SOFT COMPUTING,2019,23,13,:5035-5051. |
APA | Zhang Y,Guo DL,Sun ZX,&Chen DW.(2019).A novel CACOR-SVR multi-objective optimization approach and its application in aerodynamic shape optimization of high-speed train.SOFT COMPUTING,23(13),5035-5051. |
MLA | Zhang Y,et al."A novel CACOR-SVR multi-objective optimization approach and its application in aerodynamic shape optimization of high-speed train".SOFT COMPUTING 23.13(2019):5035-5051. |
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