RDR helps find unreachable or redundant rules.
RDR帮助查找不可用或冗余的规则。
Thus, the rule set developer needs to be aware of such cases while implementing RDR.
因此，规则集开发人员在实现 RDR 时需要了解这些情况。
RDR implementation allows the rule set to evolve as rules are properly placed and clustered.
RDR实现支持在恰当地放置和集群规则时，不断演化规则集。
The sequential single subroutine has been modularized to several subroutines with help of RDR.
顺序单一子例程已借助RDR模块化为多个子例程。
RDR also helps you identify the most frequent rules used and helps you put them at the beginning.
RDR还可帮助您识别最常使用的规则，帮助您将它们放在开头部分。
The following code shows the sample rule set written in QualityStage for standardizing part names without RDR.
以下代码显示了在QualityStage中编写的示例规则集，用于标准化没有RDR的部件名称。
RDR allows us to capture the characteristics of new data in the form of exceptions added to the default rule set.
RDR允许我们以添加到默认规则集的异常的形式捕获新数据的特征。
The RDR framework allows you to incrementally patch existing rules or add exceptions without breaking other rules.
rdr框架允许您以递增方式修补现有的规则或添加例外，且无需破坏其他规则。
Figure 3 shows how RDR helps identify cases where a new rule is required and how the rule can be patched for a new source.
图3显示了RDR规则如何帮助识别需要一条新规则的情形，如何为新来源修补规则。
An RDR-implemented rule set is also very easy to maintain as rule set developers know the exact location where a new rule is required.
RDR实现的规则集也很容易维护，只要规则集开发人员知道需要新规则的准确位置。
Rotational Dynamic Recrystallization (RDR) mechanism which based on mechanics assistance can well explain the microstructure evolution within the ASB.
一种基于力学辅助的旋转式动态再结晶(rdr)机制可以很好的解释as B内组织的演化过程。
A Rotational Dynamic Recrystallization (RDR) mechanism which based on mechanics assistance can well explain the microstructure evolution within the ASB.
一种基于力学辅助的旋转式动态再结晶(rdr)机制可以很好的解释as B内组织的演化过程。
In an RDR approach, the domain experts process the cases, make a recommendation, and provide some features, if necessary, to justify their recommendation.
在RDR方法中，领域专家会处理各种案例，给出相关建议，并在必要时提供一些功能来证明其建议的合理性。
Offering a friendly howdy, picking wild herbs or taming a bucking bronco isn't just busywork — those actions make the world of RDR feel real and yet bygone.
来一句友好的问安、采摘野生草药或驯服不羁的野马已不仅仅是为了打发时间——这些场景使“荒野大镖客：救赎”的世界感觉真实但又如同往事。
But if you write rules using an RDR framework, you know exactly where a rule is to be added, and it becomes easier to debug which rule is breaking the logic.
但是如果您使用rdr框架编写规则，就会准确知道在何处添加规则，从而可以更轻松地对破坏逻辑的规则进行调试。
As Figure 1 shows, in an RDR approach, the domain experts process the cases, make a recommendation (new rule), and provide some features to justify their recommendation.
如图1所示，在RDR方法中，领域专家会处理案例，给出相关建议(新规则)，并提供一些功能来证明其建议的合理性。
The RDR methodology allows incremental changes to the knowledge base (RuleSet) without causing unwanted side effects to the existing knowledge base or existing rule set.
RDR方法允许对知识库(RuleSet)进行增量更改，不会导致对现有知识库或现有规则集的不想要的副作用。
The first step for implementing RDR is to annotate the pre-written rules so they can be marked and we can calculate the frequency of each rule fired for the particular dataset.
实现RDR的第一步是标注预先编写的规则，以便标记它们，我们也可以计算为特定数据集触发每条规则的频率。
The basic philosophy behind RDR is based on the observation that experts do not explain how they wrote a rule but they justify that a rule is correct and provide the justification in context.
rdr背后的基本哲学基于这样的观察结果，专家不会解释他们编写规则的方式，但他们会证明规则是正确的，并在上下文内提供证据。
The first step for implementing the RDR on a particular set of rules is to cluster similar rules together, which helps to group rules in a single cluster, removing dependencies from each other.
在特定规则集上实现RDR的第一步是将类似规则聚合到一起，这有助于将规则分组到单个集群中，删除彼此的依赖关系。
The first step for implementing the RDR on a particular set of rules is to cluster similar rules together, which helps to group rules in a single cluster, removing dependencies from each other.
在特定规则集上实现RDR的第一步是将类似规则聚合到一起，这有助于将规则分组到单个集群中，删除彼此的依赖关系。
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