| 基于格网化邻域查询的海上船舶救援搜索方法 |
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| 引用本文： | 周为峰,隋芯,郭小天,姜亚洲,程田天.基于格网化邻域查询的海上船舶救援搜索方法[J].地球信息科学,2021,23(8):1422-1432. |
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| 作者姓名： | 周为峰 隋芯 郭小天 姜亚洲 程田天 |
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| 作者单位： | 1.中国水产科学研究院东海水产研究所,上海 2000902.上海海洋大学海洋科学学院,上海 2013063.浙江海洋大学信息工程学院,舟山 316022 |
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| 基金项目： | 国家重点研发计划项目(2019YFD0901405);国家重点研发计划项目(2020YFD0901202);中央级公益性科研院所基本科研业务费专项(东海水产研究所)(2019T03) |
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| 摘 要： | 海洋渔业是高风险行业,各类海洋灾害频繁发生,海上航行、作业环境复杂,因此,海上快速救援对保护渔民的生命财产安全具有重要意义。本文基于空间剖分的格网化编码,提出一种根据有效救援距离和失事船舶位置进行邻域搜索以查找失事船只相邻和最邻近可供救援的船只的方法,其中有效救援距离通过救援船舶的类型和航速来设定,根据有效救援距离设置不同的编码搜索长度。本文将模拟实验区域设定为我国东海海域,随机生成1×104个船位点,在时间检索效率和内存占用两方面,实验结果表明,与传统的船舶间距离的计算方法相比,基于格网化邻域搜索的查询方法编码后船位数据较编码转换前船位数据占用内存空间减少56.47%,同时,编码后检索运算的用户时间是编码前用户时间的17.67%,因此,基于格网化邻域搜索的查询方法占用内存小,且运算效率较高,能够有效提升对遇险船舶邻域救援船只的查询效率。
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| 关 键 词： | 船舶救援 有效救援距离 格网化 船位编码 邻域搜索 最邻近搜索 时间效率比较 内存占用 |
| 收稿时间： | 2020-11-16 |
Searching Method for Marine Ship Rescue based on Grid Neighborhood Query |
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| ZHOU Weifeng,SUI Xin,GUO Xiaotian,JIANG Yazhou,CHENG Tiantian.Searching Method for Marine Ship Rescue based on Grid Neighborhood Query[J].Geo-information Science,2021,23(8):1422-1432. |
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| Authors: | ZHOU Weifeng SUI Xin GUO Xiaotian JIANG Yazhou CHENG Tiantian |
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| Institution: | 1. East China Sea Fishery Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China2. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China3. School of Information Engineering, Zhejiang Ocean University, Zhoushan 316022, China |
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| Abstract: | Marine fishery is a high-risk industry with various marine disasters occurring frequently. Furthermore, maritime navigation and operating environment are complicated. Therefore, rapid maritime rescue is of great significance to protect the life and property of fishermen. Based on the grid coding of spatial division, this paper proposes a method to search the neighborhood based on the effective rescue distance and the location of the wrecked ship to find the ships that are adjacent to the wrecked ship and the closest neighbor for rescue. The effective rescue distance is set by the type and speed of the rescue ship. Then, the different code search lengths are set according to the effective rescue distances. In this paper, East Sea is set as the simulation experiment area, within which 10 000 ship locations are randomly generated. In terms of time retrieval efficiency and memory occupation, the experimental results show that, compared with the traditional method of calculating the distances among ships, the memory space occupation by the ship position data after encoding conversion in our proposed method is 56.47% less than that before the encoding conversion. In the meantime, the user retrieval calculation time after encoding is only 17.67% of that before the encoding. Therefore, after the ship position is encoded, the proposed method occupies a smaller memory and has a higher computational efficiency, which can greatly improve the efficiency searching for rescue ships in the vicinity of the wrecked ship. |
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| Keywords: | ship rescue effective rescue distance grid code ship position code neighborhood search nearest neighbor search time efficiency comparison memory usage |
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