| 基于广义回归神经网络与遗传算法的玻璃钢渔船船型要素优化研究 |
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| 引用本文： | 李纳,陈明,刘飞,林焰,谌志新.基于广义回归神经网络与遗传算法的玻璃钢渔船船型要素优化研究[J].船舶工程,2012,34(4):18-20. |
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| 作者姓名： | 李纳 陈明 刘飞 林焰 谌志新 |
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| 作者单位： | 中国水产科学研究院渔业机械仪器研究所,上海,200092;大连理工大学船舶CAD工程中心,大连,116024;大连理工大学船舶CAD工程中心,大连116024;大连理工大学工业装备结构分析国家重点实验室,大连116024 |
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| 基金项目： | 国家公益性行业科研专项(渔业节能关键技术研究与重大装备开发,201003024) |
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| 摘 要： | 利用神经网络的非线性拟合能力,建立了基于广义回归神经网络的"船型要素-船体阻力"数学模型,提高了模型的拟合精度。同时结合遗传算法的非线性寻优能力,利用改进的遗传算法完成了船型要素的优化设计。优化结果可以作为玻璃钢渔船初步设计的技术参考。
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| 关 键 词： | 船型要素 船体阻力 广义回归神经网络 遗传算法 |
| 收稿时间： | 2011/12/13 0:00:00 |
| 修稿时间： | 1/15/2012 4:24:55 PM |
The research of the ship parameters optimization for FRP fishing vessels based on GRNN and genetic algorithm |
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| LI N,CHEN Ming,and LIN Yan.The research of the ship parameters optimization for FRP fishing vessels based on GRNN and genetic algorithm[J].Ship Engineering,2012,34(4):18-20. |
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| Authors: | LI N CHEN Ming and LIN Yan |
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| Institution: | LI Na1,CHEN Ming2a,LIU Fei2a,LIN Yan2,SHEN Zhi-xin1(1.Fishery Machinery and Instrument Research Institute,Chinese Academy of Fishery Sciences,Shanghai 200092,China;2.Dalian University of Technology,a.Ship CAD Engineering Center,b.State Key Laboratory of Structural Analysis for Industrial Equipment,Dalian 116024,China) |
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| Abstract: | The mathematical model of "ship parameters-ship resistance" for FRP fishing vessels,based on generalized regression neural networks(GRNN),is established by using the nonlinear fitting ability of neural networks to improve the model fitting precision.At the meantime,the ship parameters’ optimizing design is accomplished by the improved genetic algorithm(GA) with its nonlinear optimization ability.The optimized results can be used as the reference for the preliminary design of FRP fishing vessels. |
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| Keywords: | ship parameters ship resistance GRNN genetic algorithm |
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