Information Integration Method Of Garden Plant Specimen Based On Data Mining

文献类型： 外文期刊

第一作者： Wu, Xiaoqing

作者： Wu, Xiaoqing;Sun, Xiang;Sun, Xiang

作者机构：

关键词： Data mining; landscape architecture; plant specimen; information integration

期刊名称：2020 5TH INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2020)

ISSN：

年卷期： 2020 年

页码：

收录情况： SCI

摘要： Aiming at the problems of large amount of plant specimen information, time-consuming information integration and poor effect, this paper proposes a method of information integration of garden plant specimen based on data mining. The data mining method is used to collect the feature information of plant samples. According to the feature parameters, the correlation values of plant categories are classified, and the corresponding information processing platform is established to improve the efficiency of information sample integration and improve the effect of information integration. The experimental results show that the method proposed in this paper can effectively solve the problem that the traditional method takes too much time, and the integration coverage is higher, which fully meets the research requirements.

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