中国舰船研究2024，Vol.19Issue(6)：64-73,10.DOI:10.19693/j.issn.1673-3185.04050
基于自组织映射和K-means聚类的分层设计空间动态缩减方法及其在船型优化中的应用
Hierarchical space reduction method based on self-organizing maps and K-means clustering for hull form optimization
摘要
Abstract
[Objective]Due to its high-dimensional,computationally expensive,and'black-box'characterist-ics,hull form optimization based on CFD usually leads to low efficiency and poor quality.To solve the above problems,this paper proposes a hierarchical space reduction method(HSRM)based on the self-organizing maps(SOM)method and K-means clustering.[Method]The visualization results of SOM are clustered and the regions of interest are extracted.In this way,data mining is used to extract the knowledge implicit in the sample simulation data which can then be used to guide hull form optimization and improve its efficiency and quality.The proposed method is applied to the hull form optimization of a 7500-ton bulk carrier.[Results]The results show that the total drag of the optimal hull form obtained using traditional particle swarm optimiz-ation(PSO)and HSRM is reduced by 1.854%and 2.266%respectively,with HSRM leading to a higher-qual-ity optimized solution.[Conclusion]The proposed method can guide the optimization algorithm to search in the direction of the optimal solution,effectively improving the efficiency and quality of optimization.关键词
船舶设计/船型优化/自组织映射/设计空间缩减/聚类分析/分层设计空间动态缩减方法Key words
naval architecture/hull form optimization/self-organizing maps/design space reduction/cluster analysis/hierarchical space reduction method分类
交通工程引用本文复制引用
于群,李鹏,郑强,冯佰威,邱春良,曾大连..基于自组织映射和K-means聚类的分层设计空间动态缩减方法及其在船型优化中的应用[J].中国舰船研究,2024,19(6):64-73,10.基金项目
国家自然科学基金资助项目(51979211,52271327,52271330,52471339,52401390) （51979211,52271327,52271330,52471339,52401390）
装备预研教育部联合基金(青年人才)资助项目(8091B032201) （青年人才）
高等学校学科创新引智计划资助项目(BP0820028) （BP0820028）
广西重大科技专项资助项目(AA23023013,AA23062037) （AA23023013,AA23062037）
中央高校基本科研业务费专项资金资助项目(104972024RSCbs0010) （104972024RSCbs0010）
国家资助博士后研究人员计划C档资助项目(GZC20232018) （GZC20232018）
