基于复杂网络的统计信息数据挖掘的研究

Research of statistic information data mining based on complex network

统计信息是区域可持续发展中重要的信息资源,涵盖了人口、农业、工业、经济等各类数据.从大量的统计信息中挖掘出更多有价值的信息,从而得到决策支持依据.通过统计信息数据挖掘的研究,从理论和仿真两方面探讨复杂网络理论在统计学研究中应用的一种.阐述基于统计数据构建社会经济系统网络的概念和复杂网络的度及其分布、平均路径长度、集群系数和介数等统计性质,挖掘这些性质在社会经济网络中的统计规律和性质,并给出复杂网络研究在决策和管理中的指导意义.

Statistic information is an important information resource for sustainable development of an area, which covers various data of population, agriculture, industry and economy. More valuable statistic information can be excavated out from a great deal of statistic information. Accordingly decisionmaking basis is got. By studying on digging statistic information data, the application of complex network to the study on statistics can be probed into in terms of theory and emulation. With this we can explain conception of constructing social economy system network based on statistic data and the statistic laws and characters of degree and distribution, average path length, clustering coefficient. We can also excavate these characters in social economy system network＇s statistic rules. Meanwhile the guidance of decision making and managing of complex network study is given.