中国舰船研究2024，Vol.19Issue(6)：45-55,11.DOI:10.19693/j.issn.1673-3185.03718
基于智能模糊推理系统的船型概念方案快速生成研究
Rapid ship hull conceptual scheme design based on intelligent fuzzy inference system
摘要
Abstract
[Objective]Aiming at the problem that it is difficult to model user requirements with fuzzy char-acteristics in existing ship conceptual scheme design(SCSD),this study focuses on a rapid SCSD system based on a fuzzy inference system(FIS)that can quickly obtain ship performance values that meet the user re-quirements and generate the corresponding ship hull design parameter values.[Methods]First,the existing ship hull parameter data is collected and sorted as prior knowledge for hyper-parameter initialization in the process of user requirement modeling.Second,based on the fuzzy set theory,the user requirements are quant-itatively mapped to the fuzzy space,and the sorted prior knowledge is used to infer the ship performance val-ues that meet the user requirements in an interpretable way.Finally,the best ship hull design parameters are matched for each ship performance value that meets the user requirements,and through the"AND"principle in fuzzy set theory,the ship design parameters that meet all the user requirements for ship performance are fur-ther inferred and taken as the SCSD.[Results]The experimental results show that the intelligent FIS can quickly infer multiple SCSDs with deviations within 3.5%according to the fuzzy user requirements within 30 seconds.[Conclusions]The intelligent FIS quantifies the fuzziness in user requirements,and after two stages of inference,the SCSD that meets the various user requirements is efficiently generated.The results of this study can provide useful references for rapid intelligent SCSD generation.关键词
船舶设计/人工智能/船舶性能要求/船型设计参数/船型概念方案生成/模糊集理论/模糊规则Key words
naval architecture/artificial intelligence/ship performance requirement/ship hull design para-meter/ship hull conceptual scheme generation/fuzzy set theory/fuzzy rule分类
交通工程引用本文复制引用
杨萌,龚俊斌,曹晋,周塔..基于智能模糊推理系统的船型概念方案快速生成研究[J].中国舰船研究,2024,19(6):45-55,11.基金项目
国防基础科研计划资助项目(JCKY2020206B037) （JCKY2020206B037）
国家春晖计划项目(HZKY20220133) （HZKY20220133）
江苏省自然科学基金面上项目资助(BK20191200,BK20241831) （BK20191200,BK20241831）
