使用BeanInfo使您的应用程序对象具有更易于阅读的属性名，并隐藏那些程序员可以使用、而规则编写者不应该使用的属性。
Use a BeanInfo to give your application objects more human readable property names and to hide properties which should be available to programmers, but not rule authors.
与应用程序对象非常相似，将对资源进行自检，以获得要在规则编辑器中显示的属性列表。
Much like application objects, the resource is introspected for the list of properties to show in the rule editor.
应用程序对象的属性可以进行配置，可以在可见性规则中使用，或在选择规则中用作需要进行匹配的值。
Properties of application objects can be profiled, used in visibility rules, or used as a value to match against in a selection rule.
最后应用粗糙集理论来对决策信息表进行离散化处理和属性约简，以生成图像分割算法选取的决策规则。
Finally, rough set theory is applied to discretization and attribution reduction of decision information table, in order to make the decision rule of image segmentation algorithm selection.
接下来本文讨论如何确定借阅记录中与借阅图书类型相关的读者属性并应用MAR_LCR算法对借阅记录进行关联规则的挖掘。
A discussion is made on how to identify relevant reader attributes in regard of the books they checked out and MAR_LCR algorithm is applied to the circulation records to mine the association rules.
对数量型属性，应用竞争聚集算法将数量型属性划分成若干个模糊集，并系统地提出加权模糊关联规则的挖掘算法。
As for quantitative attributes, they are divided into several fuzzy sets by the competitive agglomeration algorithm, and then the algorithm for mining weighted fuzzy association rules is provided.
选择要应用下面规则的属性。规则会照它们在列表中的顺序处理。
Select the attribute to which the following rules will be applied. Rules are processed in the order they appear in the list.
应用聚类方法研究了数量关联规则提取过程中的连续属性离散化问题。
This paper presents a cluster method for discretization in the processing of mining quantitative association rules.
如果指定该属性，关闭(不应用)样式规则到文档中的元素。
If set, disables (does not apply) the style rules to the Document that are specified within the element.
这些属性提供了可用于修改应用程序的本地化规则和提示。
These properties provide rules and hints for localization, which can be used to modify the application.
通过粗糙规则集的不确定性量度，应用遗传算法求取相对属性约简，然后根据所给阈值导出粗糙规则集，并对阈值对规则集的影响进行了事后分析。
With uncertain measurement of rough rules set, relative attribute reduction is obtained by applying GA, and then rough rules set is deduced under the threshold values.
通过粗糙规则集的不确定性量度，应用遗传算法求取相对属性约简，然后根据所给阈值导出粗糙规则集，并对阈值对规则集的影响进行了事后分析。
With uncertain measurement of rough rules set, relative attribute reduction is obtained by applying GA, and then rough rules set is deduced under the threshold values.
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