邓吉秋

个人信息Personal Information

副教授

博士生导师

硕士生导师

教师英文名称:Jiqiu Deng

教师拼音名称:Deng Jiqiu

电子邮箱:

入职时间:1999-06-01

所在单位:地球科学与信息物理学院

学历:博士研究生毕业

办公地点:岳麓山校区地学楼/潇湘校区地球科学大楼

联系方式:13874950729;QQ:188662140

学位:博士学位

在职信息:在职

毕业院校:中南大学

学科:地质资源与地质工程
测绘科学与技术

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Multiple Geographical Feature Label Placement Based on Multiple Candidate Positions in Two Degrees of Freedom Space

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DOI码:10.1109/ACCESS.2021.3120289

发表刊物:IEEE Access

关键字:Feature label placement,NP-hard problem,discrete differential evolution and genetic algorithm,multiple candidate positions,two degrees of freedom space

摘要:Automatic multiple geographical feature label placement (MGFLP) is a combinatorial optimization problem shown to be an NP-hard problem, and it is a challenge in automatic cartography. Many automatic label placement algorithms for point, line, and area features were put forward. It is a common way to use multiple candidate positions (MCP) for label placement, but the research in this way mostly focuses on point features and does not take all three types of features and all the possible candidate positions into account on the map. Therefore, in this paper, the concept of degrees of spatial freedom for feature label placement is proposed based on the idea of degrees of freedom of mechanical motion. We define the degrees of freedom (DOF) and its space for feature labels on a planar map so as the potential space, including all the optional candidate positions of each feature label, can be standardized. Based on two degrees of freedom (2-DOF) space, feature reference position (FRP), and certain buffer distance (CBD) from FRP, we studied the methods including generating, calculating, evaluating, and selecting MCP for feature label. By using and improving the discrete differential evolution genetic algorithm (DDEGA), we carried out MGFLP experiments on the same dataset used by DDEGA algorithm. The results show that: 1) although the MCP based on the 2-DOF space increase the complexity of the NP-hard problem, however, the obtained results by optimizing the performance of the algorithm and increasing the number of candidate positions are still better than the traditional 8-candidate positions model. 2) In the same 2-DOF space, increasing the candidate positions from less to more along each direction of the 2-DOF space improves the quality of label placement.

合写作者:Zhiyong Guo, Mohammad Naser Lessani*

第一作者:Jiqiu Deng

论文类型:期刊论文

文献类型:J

卷号:9

页面范围:144085-144105

是否译文:

发表时间:2021-10-14

收录刊物:SCI

发布期刊链接:https://ieeexplore.ieee.org/document/9570288