1) attribute weight frequency
属性加权频率
1.
Both of attribute weight frequency and strong compressible set are used to simplify discernibility matrix so that computing complexity is decreased and reduction efficiency is.
同时利用属性加权频率和强等价集概念化简区分矩阵,既减小了计算复杂度又提高了约简效率。
2) weighted frequency
加权频率
3) Attributes Weighted
属性加权
1.
Improved K-Means Algorithm based on the Attributes Weighted
基于属性加权的改进K-Means算法
4) attribute frequency
属性频率
1.
A decision tree algorithm based on attribute frequency splitting;
一种基于属性频率划分的决策树算法
2.
Decision tree algorithm using attribute frequency splitting and information entropy discretization
属性频率划分和信息熵离散化的决策树算法
3.
The definitions of the simple decision table and the attribute frequency function based on binary discernibility matrix are provided.
指出支天云的二进制可分辨矩阵约简算法存在的不足,给出简化的决策表定义和基于二进制可分辨矩阵的属性频率函数的定义。
5) frequency attribute
频率属性
1.
This paper presents in-depth research on that by frequency attribute analysis and finds out the reflected differences.
用频率属性分析技术对其进行了深入的研究,揭示了它与下部地层的反射区别,通过对三维地震数据体进行处理,确定出这套砾岩体的标志并圈定了平面分布范围。
6) wind direction frequency weighted
风向频率加权
1.
A wind direction frequency weighted(WDFW) method based upon the atmosphere wind direction frequency characteristics,combining with solving the 3D Navier-Stokes equations,the mass and heat transfer equations as well as the standard k-ε turbulence models was proposed to model the local airflow and the dispersion of vehicular exhausted plume under real atmospheric conditions.
根据大气风向频率特征,提出风向频率加权(W DFW)方法,结合求解三维N-S方程、传热传质的对流扩散方程和k-ε湍流模型来预测实际大气条件下局地大气流动和污染物扩散规律,并与现场采样分析结果进行对比。
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参考词条