| 基于改进K近邻算法的船舶通航环境智能识别 |
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| 引用本文： | 王壮,李嘉源,黄连忠,王凯,姜雅乔,马冉祺.基于改进K近邻算法的船舶通航环境智能识别[J].上海海事大学学报,2020,41(3):36-41. |
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| 作者姓名： | 王壮 李嘉源 黄连忠 王凯 姜雅乔 马冉祺 |
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| 作者单位： | 大连海事大学轮机工程学院,辽宁大连 116026;大连海事大学轮机工程学院,辽宁大连 116026;大连海事大学轮机工程学院,辽宁大连 116026;大连海事大学轮机工程学院,辽宁大连 116026;大连海事大学轮机工程学院,辽宁大连 116026;大连海事大学轮机工程学院,辽宁大连 116026 |
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| 基金项目： | 国家自然科学基金（51909020）；中央高校基本科研业务费专项资金（3132019194）;无人船协同创新研究院种子基金（3132019009）;辽宁省自然科学基金（2019 BS 023）; 长江航道局科技项目（201930004） |
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| 摘 要： | 为实现船舶能效的智能优化,从船舶通航环境出发,研究船舶通航环境的智能识别方法。基于所获得的船舶通航环境大数据,建立基于改进K均值聚类算法的船舶通航环境类别知识库,设计相关系数加权的K近邻算法,实现船舶通航环境的智能识别。实例分析结果表明,此基于改进K近邻算法的智能识别方法的识别准确率可达97.25%,相对于未改进的K近邻算法,准确率提高7.81%。所提出的智能识别方法可为基于通航环境智能识别的船舶分段航速智能优化方法的研究奠定基础。
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| 关 键 词： | 通航环境 K均值聚类 K近邻算法 智能识别 |
| 收稿时间： | 2020/1/6 0:00:00 |
| 修稿时间： | 2020/7/3 0:00:00 |
Intelligent identification of ship navigation environment based on improved K-nearest neighbor algorithm |
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| wang zhuang,LI Jia-Yuan,HUANG Lian-Zhong,WANG Kai,JIANG Ya-qiao and MA Ran-Qi.Intelligent identification of ship navigation environment based on improved K-nearest neighbor algorithm[J].Journal of Shanghai Maritime University,2020,41(3):36-41. |
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| Authors: | wang zhuang LI Jia-Yuan HUANG Lian-Zhong WANG Kai JIANG Ya-qiao and MA Ran-Qi |
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| Abstract: | In order to realize the intelligent optimization of ship energy efficiency, starting from the ship navigation environment, the intelligent identification method of the ship navigation environment is studied. Based on the obtained ship navigation environment big data, a knowledge base of ship navigation environment categories based on the improved K means clustering algorithm is established, and a K nearest neighbor algorithm weighted by correlation coefficients is designed to realize the intelligent identification of ship navigation environment. The example analysis results show that, the identification accuracy of the intelligent recognition method based on the improved K nearest neighbor algorithm can reach 97.25%, which can increase the accuracy rate by 7.81% compared with the unimproved K nearest neighbor algorithm. The proposed intelligent identification method can lay the foundation for the research on the intelligent optimization method of ship segmentation speed based on the intelligent identification of navigation environment. |
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| Keywords: | navigation environment K-means clustering K-nearest neighbor algorithm intelligent identification |
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