自组织数据挖掘与回归分析方法的比较研究  

Comparison between the self-organizing data mining and regression analysis

作　　者：郑明翠[1] 贺昌政[1] 

机构地区：[1]四川大学工商管理学院,四川成都610064

出　　处：《系统工程与电子技术》2005年第10期1748-1751,共4页Systems Engineering and Electronics

基　　金：国家自然科学基金资助课题(70271073)

摘　　要：采取定性分析、理论分析和实验研究相结合的方式,从三方面对自组织数据挖掘方法与回归分析方法进行比较:包括二者的算法过程,对不同对象的拟合和预测效果以及二者的联系。结果不仅揭示了二者的区别和联系,而且表明,自组织数据挖掘方法是复杂系统模拟预测的有效工具。The qualitative analysis, theoretic analysis and experimental research are exerted to do the comparison between the above two methods from three aspects, including the algorithm process, the approximating and forecasting effect in different objects, and the relationship. The result unveils the difference and relationship between the self-organizing data mining and regression analysis, it also proves that self-organizing data mining is an efficient approach to the research on approximating and forecasting of complex systems.

关 键 词：自组织数据挖掘 回归分析 拟合与预测 复杂系统 

分 类 号：N94[自然科学总论—系统科学]