天津建设科技2025，Vol.35Issue(3)：76-80,5.DOI:10.3969/j.issn.1008-3197.2025.03.018
基于模糊聚类和遗传算法的土地测绘数据分类集成方法研究
Research on Land Surveying and Mapping Data Classification Integration Method Based on Fuzzy Clustering and Genetic Algorithm
葛彤 1许洋1
作者信息
- 1. 北京世纪千府国际工程设计有限公司 天津分公司,天津 300074
- 折叠
摘要
Abstract
In order to improve the accuracy and completeness of the land surveying data,preprocessing the original land surveying data,noise,redundancy,and abnormal data were removed.Subsequently,utilizing DSM parallel technology to efficiently extract feature information from land surveying data,fuzzy clustering algorithm was combined to classify land surveying and mapping data.Finally,the integration optimization of classification re-sults was achieved through genetic algorithms.The results showed that the maximum accuracy of the proposed method for land surveying and mapping data classification was 95%,and the maximum evaluation value for the quality of land surveying and mapping data integration was 0.96,confirming that the proposed method has better performance in land surveying and mapping data classification integration.关键词
模糊聚类/土地测绘/分类集成/遗传算法Key words
fuzzy clustering/land surveying/classification integration/genetic algorithm分类
天文与地球科学引用本文复制引用
葛彤,许洋..基于模糊聚类和遗传算法的土地测绘数据分类集成方法研究[J].天津建设科技,2025,35(3):76-80,5.
