首页> 外文会议>International Conference on Intelligent Computing and Control Systems >Empowerment of Digital Technology to Improve the Level of Agricultural Economic Development based on Data Mining
【24h】

Empowerment of Digital Technology to Improve the Level of Agricultural Economic Development based on Data Mining

机译:基于数据挖掘的农业经济发展水平赋予数字技术权力

获取原文

摘要

Rural economic development is of the great significance to local regional economic development and Rural Revitalization Strategy. The main task of multi-scale data mining has two aspects, namely, multi-scale realization of data and multi-scale discovery of knowledge: the former belongs to data preprocessing, which can be realized by data scale division. The latter needs to improve the specific mining technology, excavate knowledge in the multi-scale representation of data, analyze and deduce the relationship between knowledge. How to find the valuable information in the mass data and the security risks in the network is one of the problems to be solved in the information processing technology. The clustering analysis method in data mining technology is to cluster the data with high similarity according to the similarity measurement standard. Therefore, the data objects in the same cluster are more similar to those in different clusters. With the prevalence of supply side reform and the implementation of Rural Revitalization Strategy, the agriculture of the primary industry takes advantage of the situation. From the perspective of urban-rural system, rural development plays an important role in the growth of cities and regions. This paper uses data mining technology to improve the level of agricultural economic development.
机译:农村经济发展对地方区域经济发展和农村振兴战略具有重要意义。多尺度数据挖掘的主要任务有两个方面,即多规模的数据实现和知识的多种发现:前者属于数据预处理,可以通过数据刻度划分实现。后者需要改善特定的采矿技术,挖掘知识在数据的多规模表示,分析和推断知识之间的关系。如何在信息处理技术中找到群众数据中的有价值的信息和网络中的安全风险之一是在信息处理技术中解决的问题之一。数据挖掘技术中的聚类分析方法是根据相似度测量标准聚类具有高相似性的数据。因此,同一群集中的数据对象与不同群集中的数据对象更类似。随着供应方改革的普遍存在和农村振兴战略的实施,主要产业的农业利用了这种情况。从城乡系统的角度来看,农村发展在城市和地区的增长中发挥着重要作用。本文采用数据挖掘技术来提高农业经济发展水平。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号