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1·A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.

提出了基于最大互信息熵且具有奇数约束的优化得分函数。

2·Information entropy indicates the terrain variety in a certain direction.

信息熵表征了在某一具体方向上的地形变化情况。

3·MIBARK algorithm defined the attribute importance using the information entropy.

MIBARK算法基于信息论的方法，用信息熵来定义属性的重要性。

4·The information entropy of land use structure varies significantly with the town.

各个镇之间土地利用结构信息熵也具有明显差异。

5·A distribution function of droplet volume was derived using the information entropy.

采用最大熵原理，推导出喷雾场液滴体积分布函数。

6·Using fuzzy probability measure, an information entropy of assessment was introduced.

运用模糊随机可测理论度量了评价系统的不确定熵。

7·And then a relative attribute reduction algorithm is mentioned based on information entropy.

后面又提到了基于信息熵的相对属性约简算法。

8·In this paper, information entropy is introduced for feature evaluation and a new method TF.

文章引入信息熵，提出了针对单文本的特征评价方法TF。

9·With the number of state increasing, the information entropy tends towards its intrinsic entropy.

随状态数增加，信息熵趋向固有熵。

10·The information entropy of measured quantity and measuring result, and the error entropy are defined.

给出被测量信息熵、测量误差熵和测量结果信息熵的定义、相互关系以及求解方法。