一种模型是基于有效性测度谢白尼指数的基因表达数据的模糊聚类分析。
One model is fuzzy cluster analysis of gene expression data based on a cluster validity measure named Xie-Beni index.
分析结果表明模糊相似性指数方法能够比动态相似性指数方法获得更长的预测时间和更低的错误预测率。
The result shows that the fuzzy similarity index is better than dynamical similarity index in increasing anticipation time and decreasing false prediction rate for the prediction of epileptic seizure.
在回顾了大多数模糊性的信息熵度量定义之后，首次定义了模糊互熵和信息传输指数等新概念。
Most of existing fuzzy information entropy definitions are reviewed before fuzzy mutual entropy and information transmission index are introduced for the first time.
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