【作者】 王明宇；

【导师】 吴燕；

【作者基本信息】 北京林业大学 ， 管理科学与工程， 2010， 硕士

【摘要】 本研究是在原有全国林业行政人员执法管理系统(下文简称“系统”)的基础上,以数据挖掘理论及技术为支撑点,本着对系统中数据进行详细分析与深入挖掘的目的进行的。研究中主要用到了数据统计法、数据挖掘法、模型分析法等多种方法,主要解决以下两个问题：1、多属性关联(查询)问题。系统中,可以实现单一属性(最多能实现二维属性)的查询与简单的分析功能,属性间各种潜在的关联我们无法得知。因此,将使用数据挖掘中的关联分析法,借助clementine软件探索并实现对多属性的关联分析。同时,建立多属性查询系统。2、人员配置优化问题。各地的人员配置呈现地方特色,人员结构层次参差不齐、人员配置不合理问题突出,急需对人员的结构配置进行优化。本研究首先运用聚类分析方法,按照某些共性将全国划分成为三类,其次运用最大模糊信息熵理论建立人员配置的优化模型,最终将三类地区和最优模型进行比较。更多还原

【Abstract】 This study is based on the Management System of National Forestry Law Enforcement ("system" for short), supported by data-mining theory and technology, in the spirit of detailed analysis and in-depth data mining. Used of the data statistics, data mining, model analysis and other methods, mainly deal with the following two questions:1. Multi-attribute associations (select) problem. The "system" can achieve a single property (up to achieve two-dimensional attributes) queries and simple analysis functions, but can’t deal with the relationship between attributes potentialy. Therefore, we’ll use correlation analysis of the data mining, explore and achieve association of multi-attribute analysis with clementine software. Meanwhile, to establish multi-attribute select system.2. Staffing optimization. Staffing everywhere show local characteristics, the personnel structure differently, staffing unreasonable becomes to a serious problem, the structure of personnel needed to optimize imperatively. In this study, firstly, using cluster analysis, divided the country into three types. Secondly, using the maximum fuzzy entropy theory to make the staffing optimization model. Finaly, three regional and optimal models will be compared.更多还原