基于核主成分分析方法的标准化船型设计优化

Optimal Design of Standard Hull Pattern Based on Kernel Principal Component Analysis

合理选择船型、主尺度、船舶型线,减少船舶阻力,减少污染,降低能耗,保护环境,是船舶设计过程中应注意的十分重要的问题。但是最佳船型方案选择是一个复杂的多变量、多目标的系统优化工程。核主成分分析方法(KPCA)是目前一种常用的综合评价方法。它不仅具有优秀的主元提取性能,更尤其适合于处理非线性问题,对内河干散货运输船型设计优化具有很好的实际应用价值和指导作用。

To select hull pattern and principal scales reasonably is very important in ship design. A good selection can reduce ship resistance, lower power consumption and protect environment. The best hull pattern seletion is a complex and multi-variable process. The Kernel Principal Component Analysis （KPCA） is a comprehensive evaluation method commonly used to solve this problem. KPCA possesses excellent ability to extract main term and is suitable for solving non-linear problems. KPCA is of practical value for inland river dry bulk carrier hull pattern optimization.