由确定性退火技术构造学习规则用于优化分类器参数，目的是减少分类误差以及待识别空间的系统熵。
Learning rules are constructed according to deterministic annealing to optimize classifier parameters, on purpose to reduce classification error and system entropy of the space to be identified.
基于竞争学习算法的模糊分类器确定系统的模糊空间和模糊规则数，并得出每个样本对每条规则的适用程度。
The fuzzy space structure of system and the number of fuzzy rules based on fuzzy competitive learning algorithm are determined and the fitness degree of each rule contrast to each sample is obtained.
基于元组空间提出了一种适用于多维大规则库的包分类算法——元组向量折叠算法。
Tuple Folded Vector algorithm (TFV), introduced in this paper, is applied to multiple fields in big rule database.
本文对无过滤规则无冲突的数据库进行了研究，提出了基于元组空间多维分组分类算法：元组空间矢量位映射算法。
Based on tuple space search, a packet classification algorithm called bitmap vector of tuple space for multi dimensional conflict free filters is presented in this paper.
研究发现快速包分类算法EGT-PC由于压缩特里树路径带来规则集的大量冗余备份降低了算法的查找时间和存储空间等性能。
This paper found out the fast packet classification algorithm EGT-PC's search time and storage space performance were decreased by the rules' redundant copies.
研究发现快速包分类算法EGT-PC由于压缩特里树路径带来规则集的大量冗余备份降低了算法的查找时间和存储空间等性能。
This paper found out the fast packet classification algorithm EGT-PC's search time and storage space performance were decreased by the rules' redundant copies.
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