一种新的不完备食品信息系统评价属性相对约简算法

A New Direct Method of Attribute Relative Reduction in A Incomplete Information Table

本文针对不完备食品信息系统提出了一种基于粗糙集理论的评价属性相对约简方法。本文利用粗糙集等价关系的扩展,即容差关系为基础提出容差关系相似矩阵的概念。然后通过引入广义决策函数的限制来解决不完备信息系统约简的不一致性问题,通过容差关系相似矩阵求不完备信息系统的核属性,再利用属性在容差关系相似矩阵中出现的频率给出了属性重要度的计算公式,利用属性重要度为约简的启发式规则,并运用折半启发式算法减少扩展次数,提高约简速度。实验表明该方法是简单有效的。

For incomplete food safety information system, this paper proposes a direct method of attribute relative reduction based on rough set theory. This reduction method gives the concept of tolerance relationship similar matrix via using an extension of equivalence relationship of rough set theory, which is called tolerance relationship. It solves the problem of inconsistency in the incomplete information system through the introduction of restrictions of the generalized decision function. It calculates the core attributes of incomplete information systems via the tolerance relationship similar matrix. It applies attribute significance, which this paper puts forward based on attribute frequency in the tolerance relationship similar matrix, as the heuristic konwledge. It makes use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that this method is simple and effective.