A complete recursive algorithm for minimal reduction under graph view is designed.
本文提出图表示下的知识约简，给出图表示下求最小约简的完备递归算法。
This model reduces attributes by knowledge amount of information for a rough set, and a minimal reduction set is formed.
该模型利用粗糙集中知识白勺信息量对属性停止约简，并产生出最小约简。
Through improving and extending the process of computing core, the minimal reduction algorithm based on attribute frequency heuristic information are put forward.
对分辨矩阵求核过程进行改进与扩展，给出了一种以属性频度作为启发式信息计算最小约简快速完备方法。
It has been proved the computation of minimal reduction and full reduction both is NP-hard problem, in artificial intelligence the common way is to employ heuristic knowledge to reduce.
研究表明，最小约简的计算和全部约简的求算都是NP问题，在人工智能中，解决这类问题的一般方法是利用启发式信息进行约简。
In theory, consumers could steer firms towards waste reduction by buying products that are easy to recycle, say, or have only minimal packaging.
理论上讲，消费者购买容易回收的产品，或者是包装最简单的产品，能引导企业实现减少废弃物。
Its macro-level impact is likely to be minimal—especially as it was accompanied by a reduction in the rebates available for other, polluting products like high-grade zinc and some types of battery.
其在宏观方面的影响可能是微乎其微，特别是因为减少退税也有利于其他污染产业，如高含锌量电池以及其它类型的电池产品。
But it is a NP-Hard problem to get the minimal attribute reduction.
但求取任意问题的最小属性集是一个NP难问题。
Intervention: minimal anterolateral acromial approach to the proximal humerus, percutaneous fracture reduction, and minimally invasive application of the NCB plate.
干预：在前侧方向使肩峰最小化接近肱骨近端，经皮复位骨折，微创使用非接触桥接钢板。
Important advantages are still achieved in cycle time reduction and the ability to cast near net shape castings with minimal porosity.
最大的优点仍是减少生产周期，并且能铸造出含有最少量气孔的铸件。
Then, according to the features of the generalized information table, the algorithms of acquiring minimal attribute reduction, attribute value reduction and minimum decision algorithm are put forward.
首先介绍了决策表、广义信息表的构造及特点，然后给出了求决策表的最小属性约简及最小决策算法的计算方法。
An example shows this algorithm can achieve the minimal relative reduction of incomplete decision table.
通过实例说明，该算法能得到不完备决策表的最小相对约简。
Based on rough logic, theorems is presented, whether attribute reduction and minimal decision algorithm change or not when a new instance is added to the universe.
以粗糙逻辑为基础，首先给出了在新实例加入论域后判断约简变化与否以及判断原极小决策算法中决策规则变化与否的判定依据。
Based on rough logic, theorems is presented, whether attribute reduction and minimal decision algorithm change or not when a new instance is added to the universe.
以粗糙逻辑为基础，首先给出了在新实例加入论域后判断约简变化与否以及判断原极小决策算法中决策规则变化与否的判定依据。
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