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聚类分析在测绘地理信息领域的应用

Application of cluster analysis in the field of surveying and mapping geographic information
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摘要 介绍了聚类分析的基本原理、经典算法以及聚类结果评价体系,探讨了聚类分析在测绘地理信息领域的具体应用及其未来发展趋势与挑战。聚类分析作为测绘地理信息领域中不可或缺的数据分析工具,需要我们继续挖掘其应用潜力。同时,如何进一步提高聚类分析的效率、精度和可靠性,仍然需要积极研究与探索,并将成果用于推动测绘地理信息产业的发展与创新。 In this article,the basic principles,classical algorithms and evaluation system of clustering analysis are introduced,the specific applications of clustering analysis in the field of surveying and mapping geographic information are explored,and its future development trends and challenges are discussed.As an indispensable data analysis tool in the field of surveying and mapping geographic information,clustering analysis requires us to continue to explore its application potential.At the same time,how to further improve the efficiency,accuracy and reliability of clustering analysis still needs active research and exploration,and the achievements should be used to promote the development and innovation of the surveying and mapping geographic information industry.
作者 王赟 WANG Yun(Shanxi Institute of Surveying and Mapping Geographic Information,Taiyuan 030001,China)
出处 《经纬天地》 2024年第5期45-48,共4页 Survey World
关键词 聚类算法 K-MEANS 测绘地理信息 clustering K-means surveying and mapping geographic information
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  • 1江小平,李成华,向文,张新访,颜海涛.k-means聚类算法的MapReduce并行化实现[J].华中科技大学学报(自然科学版),2011,39(S1):120-124. 被引量:79
  • 2周涓,熊忠阳,张玉芳,任芳.基于最大最小距离法的多中心聚类算法[J].计算机应用,2006,26(6):1425-1427. 被引量:72
  • 3韩家炜,坎伯.数据挖掘概念与技术[M].北京:机械工业出版社.2008.
  • 4Srirama SN,Jakovits P,Vainikko E.使用MapReduce解决云端的科学计算问题[J].下一代计算机系统,2012,39(11):184-192.
  • 5WU X, ZHU X, WU G, et al. Data mining with big data[J]. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(1): 97-107.
  • 6CHEN M-S, HAN J, YU P S. Data mining: an overview from a database perspective[J]. IEEE Transactions on Knowledge and Data Engineering, 1996, 8(6): 866-883.
  • 7NIMMAGADDA S L, DREHER H. Petro-data cluster mining——knowledge building analysis of complex petroleum systems[C]//ICIT 2009: Proceedings of the 2009 IEEE International Conference on Industrial Technology. Washington, DC: IEEE Computer Society, 2009: 1-8.
  • 8FAHAD A, ALSHATRI N, TARI Z, et al. A survey of clustering algorithms for big data: taxonomy & empirical analysis[J]. IEEE Transactions on Emerging Topics in Computing, 2014, 2(3): 1.
  • 9KURASOVA O, MARCINKEVICIUS V, MEDVEDEV V, et al. Strategies for big data clustering[C]//ICTAI 2014: Proceedings of the IEEE 26th International Conference on Tools with Artificial Intelligence. Piscataway, NJ: IEEE, 2014: 740-747.
  • 10GUNARATHNE T, WU T-L, QIU J, et al. MapReduce in the clouds for science[C]//CloudCom 2010: Proceedings of the IEEE Second International Conference on Cloud Computing Technology and Science. Washington, DC: IEEE Computer Society, 2010: 565-572.

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