1) fuzzy weighted association rules
模糊加权关联规则
1.
Study & application of a fuzzy weighted association rules;
一种模糊加权关联规则算法及其在流程工业中的应用
2.
In order to advance the performance of association rules mining algorithm when disposing big dataset,a novel fuzzy weighted association rules mining algorithm namely FWAR is proposed.
为了提高关联规则挖掘算法处理大数据集的性能,提出一种新的模糊加权关联规则挖掘算法——FWAR算法。
3.
To monitor flowing industry s production,the large history data are analyzed by fuzzy weighted association rules algorithm.
采用数据挖掘中的模糊加权关联规则对流程企业中的设备运行数据进行分析,首先阐述了模糊理论和Apriori算法的内容,分析参数点的重要程度,找出偏离常规运行状态但未到报警界限的参数点并模糊化,得到了隶属函数截集的均值和综合加权值,然后对传统的Apriori算法进行改进,提出了加权的关联规则算法并编程实现,从而起到流程企业设备故障监控的作用。
2) fuzzy association rules
模糊关联规则
1.
Application of multidimensional time series fuzzy association rules for hot metal temperature forecasting in a blast furnace;
多维时序模糊关联规则在高炉炉温预报中的应用
2.
System for attack recognition based on mining fuzzy association rules;
一种基于模糊关联规则挖掘的攻击识别系统
3.
Mining fuzzy association rules for processing industry based on fuzzy clustering;
基于模糊聚类的模糊关联规则在流程企业中的应用
3) fuzzy association rule
模糊关联规则
1.
As the fuzzy concepts can reflect the world more naturally,the fuzzy association rules play a more important role in the data mining research fields.
关联规则发现是数据挖掘研究领域中的重要内容之一,而以自然语言描述的模糊关联规则更符合人类的思维方式,在决策中占据重要作用。
2.
In view of that the general association rules can t express the association of fuzzy data,a series of definitions of fuzzy association rules is given and an algorithm of fuzzy association rule mining is proposed based on tree structure.
针对普通关联规则不能表达挖掘对象中模糊信息的关联性问题,给出了一系列有关模糊关联规则的定义,并提出一种基于树形结构的模糊关联规则挖掘算法(FARMBT)。
3.
This paper employs fuzzy association rules mining algorithm(FARMA)to mine highly effective fuzzy rules from network data sets,and then uses the obtained rules to design and construct fuzzy classifiers for intrusion detection.
论文把模糊关联规则挖掘算法引入到网络的入侵检测,利用该算法从网络数据集中提取出具有较高可信性和完备性的模糊规则,并利用这些规则设计和实现用于入侵检测的模糊分类器。
4) fuzzy associate rules
模糊关联规则
1.
In the algorithm, each quantitative attribute is replaced by a fuzzy set and divided into several attributes, which are calculated as separate attributes of database in mining fuzzy associate rules.
阐述了在入侵检测中应用模糊关联规则挖掘的方法,提出了对传统Apriori算法的改进。
2.
In this paper, we describe the technology of mining fuzzy associate rules.
针对数据挖掘中的“尖锐边界”问题,阐述了模糊关联规则挖掘技术,提出了在模糊关联规则的挖掘中将事务属性模糊集中的元素作为单一属性来处理的方法,给出了模糊关联规则挖掘的算法。
3.
This paper describes the technology of mining fuzzy associate rules.
文中阐述了模糊关联规则挖掘技术,提出了在模糊关联规则的挖掘中将事务属性模糊集作为单一属性来处理的方法。
5) weighted fuzzy production rule
加权模糊规则
1.
A new reasoning mechanism based on the weighted fuzzy production rules is presented.
提出了一种基于加权模糊规则的新的推理机制,并将这组加权模糊规则及相应推理机制映射成了一个模糊神经网络,其中加权模糊规则中的(局部和整体)权重恰好对应于神经网络的连接权。
2.
The concept of adaptive neuro-fuzzy reasoning mechanism based on the weighted fuzzy production rules is given at first in this paper.
本文提出了基于加权模糊规则自适应神经-模糊推理机制的概念。
6) weighted association rule
加权关联规则
1.
Mining of weighted association rules based on algorithm Apriori;
基于Apriori算法的加权关联规则的挖掘
2.
Algorithm of weighted association rules mining with multiple minimum supports;
基于多最小支持度的加权关联规则挖掘算法
3.
The Application of Weighted Association Rules in Port Scanner Detection;
基于加权关联规则的端口扫描检测
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参考词条