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莆 田 学 院
毕 业 论 文
题 目 基于数据挖掘的经济普查数据分析
学生姓名 郑飞跃
学 号 510704339
专 业 计算机科学与技术
班 级 计算机2班
指导教师 黄海
二00九年四月二十一日
目 录
绪论·············································(3)
数据挖掘技术·····································(3)
研究问题分析·····································(4)
国内经济普查实践与数据分析现状···················(4)
本文研究内容及方法·······························(4)
第2章 聚类分析算法····································(4)
2.1 数据挖掘过程·····································(4)
2.2 聚类分析技术基础·································(5)
2.3 数据挖掘对聚类的要求·····························(5)
2.4 聚类方法的分类···································(6)
第3章 K均值算法········································(6)
3.1 K均值算法思想····································(6)
3.2 K均值算法流程····································(7)
第4章 K均值算法在经普数据分析上的实现··················(7)
4.1 数据的采集、预处理·······························(7)
4.2 算法演示·········································(8)
4.3 数据分析··········································(8)
第5章 K均值算法分析系统的设计··························(9)
5.1 开发工具及运行环境简介····························(9)
5.2 主界面···········································(10)
5.3 修改密码·········································(11)
5.4 运算模块·······································(12)
5.5 企业数据管理模块·······························(20)
5.6 退出登陆·······································(26)
5.7 下一步工作·····································(26)
第6章 结束语········································(26)
第7章 致谢··········································(26)
参考文献·············································(27)
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基于数据挖掘的经济普查数据分析
郑飞跃
(电子信息工程学系 指导教师:黄海)
摘要:随着全国第二次经济普查数据的上报,面对普查之后的海量数据,如何更好地利用这些数据资料,帮助国家在金融危机下制定更好的经济决策,成为目前社会各界关注的热点。将数据挖掘技术应用于经济普查数据的分析,可以找出隐含在数据中的更深层次的信息,对决策者制定决策是很有参考价值的。
关键词:经济普查 数据挖掘 决策树算法 K-均值算法
Abstract: With the countrys second economic census data to report, in the face of the huge amount of data after the survey, how to make better use of t
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