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

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【中图分类号】：P208 【文献标志码】：A 【文章编号】：1008-3197（2025）03-76-05

【DOI编码】：10.3969/j.issn.1008-3197.2025.03.018

Research on Land Surveying and Mapping Data Classification Integration Method Based on Fuzzy Clustering and Genetic Algorithm

GE Tong， XUYang

（Tianjin Branch，Beijing Century Qianfu International Engineering Design Co.Ltd.，Tianjin3Ooo74，China）

【Abstract】：Inorder toimprove theaccuracyand completenessoftheland surveying data，preprocessing theoriginal land surveying data，noise，redundancy，and abnormal data were removed.Subsequently，utilizing DSM paralel technology to eficiently extract feature information from land surveying data，fuzzy clustering algorithm was combined to classifyland surveying and mapping data.Finally，the integration optimization ofclassification results 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 ofland surveyingand mappingdata integration was O.96，confirming that theproposed method has better performance in land surveying and mapping data classfication integration.

KeyWords】： fuzzy clustering;land surveying;classification integration;genetic algorithm

一般情况下，国家多种生产建设均需落实到土地上，但是国土资源是有限的，再加之国土资源利用具有不可逆转性，使得国土资源规划难度大幅度增加。（剩余4413字）