【摘要】 道路交通数据资源日益膨胀和复杂化 ,已经远远超出了人脑的记忆和分析能力。面对道路交通的海量数据 ,传统运用的DBMS和OLTP技术 ,已无法发现隐藏在数据背后的关系、规则和发展趋势等新的内容、知识和信息。因此 ,建立基于DMKD的智能道路交通安全决策支持系统是相关部门急需解决的重大课题。笔者重点介绍了数据挖掘、知识发现的概念 ,提出了基于DW +OLAP +DMKD的道路交通安全决策支持系统 ,通过道路交通系统的要素分析 ,介绍了一种面向属性的粗糙集方法提取规则 ,并阐述了一种递进式规则评价提炼过程。更多还原

【Abstract】 Resource of road traffic data expands so rapidly that greatly exceeds people’s ability to analyze. Facing that huge amount of data, people still could not find the knowledge of relationship, regulations and developing trends hidden behind these data by traditional DBMS and OLTP techniques. It becomes an important project of urgent need for relevant department to establish an intelligent decision making supporting system for the road traffic safety based on DMKD. The concepts of data exploring and knowledge discovery are introduced, and a supporting system based on DW+OLAP+DMKD is presented. Through analyzing the elements of road traffic system, a method based on rough set of extraction rules is discussed in detail and a refinery process for rules evaluation and extraction is presented.更多还原