决策表信息系统演化模型的回归分析预测算法

粗糙集理论是一种处理不确定知识的数学工具,现在粗糙集理论大多数的研究应用都停留在静态表的基础上,但在实际中决策信息表的数据是在不停的增加更新当中,静态的方法在处理不停增加和变换的数据时有着很明显的局限性。本文着眼于研究多粒度时间序列下各个粒度所产生的决策间的相互关联性,并建立了相关的演化模型。同时利用回归分析的方法设计了预测算法。

Pre-sentient Algorithm of Regression Analysis Based on Evolvement Model of Information System of Decision Table

Rough Set is a mathematic tool to deal with uncertain knowledge.The present studies and applications remain stay within the region of static tables,but data in the real world is increasing and updating,the static has clear apparent limitations when dealing with the changed data.This paper focuses on researching on the relevance between the decisions generated by each granular under multi-granularity time series,and a related evolutionary models is built.Meanwhile a pre-sentient algorithm is designed by regression analysis method.