邓吉秋
  • 学位:博士学位
  • 职称:副教授
  • 学科:地质资源与地质工程. 测绘科学与技术
  • 所在单位:地球科学与信息物理学院

副教授 博士生导师 硕士生导师

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:校本部地学楼
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
点击次数:
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:
收录刊物:
SCI
个人简介

邓吉秋,男,湖南益阳人,博士,副教授,地理信息系副主任。

从事地学大数据与人工智能、网络GIS与移动GIS、地学三维建模与可视化等研究与教学,及相关信息系统和工程的设计与开发,侧重于资源、环境、灾害等领域。

主持或参与国家/省部级科研课题及企业合作项目共50余项,负责30余项信息系统的设计与开发;公开发表学术论文60余篇、其中SCI/EI收录30余篇,参与出版专著5部;申请发明专利40余项,授权11项。

现主持科研项目:

[1]. 山西省矿产资源调查监测中心,矿业权全生命周期信息化管理方案,技术负责,2023年11月-

[2]. 湖南省重点研发计划项目“重金属暴露对环境与健康的影响研究”,课题5:重金属来源-暴露途径-重大疾病关系链,主持,2023年7月-

[3]. 长沙有色冶金设计研究院有限公司,车辆位置刷新智能算法和GIS服务,主持,2022年12月-

[4]. 湖南省水文地质环境地质调查监测所,湖南沅陵官庄金矿床三维地质建模及成矿预测,技术负责,2022年11月-

[5]. 国家自然科学基金(42172330),面向三维成矿预测的多源异构地质资料钻孔数据智能抽取与结构化方法,主持,2022年1月-

[6]. 中大检测(湖南)股份有限公司,地质灾害智能预警及发布模块研究及原型系统,系统设计与开发,2021年9月-

[7]. 长沙普德利生科技有限公司,应急GIS地图引擎与应急指挥信息系统,主持,2021.1月-


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