The novel online heuristic algorithm of representation based on polygonal boundary reduction is presented in detail.
提出了一种新颖的可在线计算的时间序列启发式算法。
A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed.
提出了一种基于条件信息熵的知识约简启发式算法，并指出该算法的时间复杂度是多项式的。
The item of attribute frequency in the scan vector was taken as heuristic information to improve the efficiency of attributes reduction.
以扫描向量中的属性频率项作为属性约简搜索的启发信息，提高了属性约简效率。
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。
In this paper, we propose a new attributes reduction algorithm based on the significance of attribute dependencies as heuristic information and add a certain variable precision.
粗糙集理论是一种新的数据挖掘算法，文章以属性依赖重要性作为启发信息提出了一种新的属性约简算法，且加入了一定的分类正确度。
The minimum attributes reduction set is expected to acquire the brief regulated set. This is taken as NP-hard Problem, which can be figured out through the heuristic algorithm.
为了获得简明的规则集，通常希望能找出最小的属性约简集，而求解最小约简是NP难问题，解决此类难题通常采用启发式算法以求得近似最优解。
After that we study on the ordered decision table and propose a new heuristic attribute reduction algorithm based on dominance matrix, whose time complexity is polynomial.
再次，对有序决策表进行了研究，提出了一种基于优势矩阵的启发式属性约简算法。
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。
The paper offer a new heuristic attribute reduction algorithm based on conditional granularity entropy, though running an example, we show that this algorithm is effective.
提出了一种基于条件粒度熵的属性约简的启发式算法，通过例子分析，表明该算法是有效的。
Based on conditional information quantity, a heuristic algorithm for assignment reduction is presented, and the complexity of this algorithm is analyzed.
给出了分配约简的一种启发式算法：条件信息量约简算法，分析了该算法的时间复杂度。
In this paper, a heuristic algorithm based on decision strength, the coverage degree of condition vectors and the significance of attribute for condition vectors' reduction is proposed. Experi...
论文以决策强度、条件向量的覆盖度和属性的重要性为启发式信息，提出了条件向量约简的一种启发式算法，通过实验验证了该算法是有效的。
In this paper, a heuristic algorithm based on decision strength, the coverage degree of condition vectors and the significance of attribute for condition vectors' reduction is proposed. Experi...
论文以决策强度、条件向量的覆盖度和属性的重要性为启发式信息，提出了条件向量约简的一种启发式算法，通过实验验证了该算法是有效的。
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