| 1. | Equivalence relations between generalized frames
广义框架之间的等价关系 |
| 2. | Some equivalence relations in markov chains in random environments
随机环境马氏链中的几种等价关系 |
| 3. | In rs , knowledge obtained is decided by the objects relationship , such as equivalence relation and simulation relations etc
知识获取是根据对象间的某种关系如等价关系、相似关系等来定义。 |
| 4. | In section one , we introduce three different definitions on the fractional chromatic coloring and prove the equivalence relation between them
在第一部分中，我们主要介绍了分数染色的三种不同定义，给出了这三者之间的等价性证明。 |
| 5. | Mining ordering rules based on ordered relations is a concrete example of application of generalizations of rough set model with non - equivalence relations
基于有序关系来挖掘有序规则可看作是粗糙集模型的非等价关系扩展的一个具体应用实例。 |
| 6. | Owing to the strong condition of equivalence relation , there exist some limits , and it has been proved to be np - hard to find all reductions and a minimal reduction
由于等价关系条件较强，有一定的局限性，已经证明求所有约简和最小约简是np - hard问题。 |
| 7. | In chapter 2 , a class of fuzzy finite automata corresponding to the mealy type of ordinary automata is formulated and two types of statewise equivalence relations are introduced
在第二章中，对应于经典mealy型有限状态自动机的一类模糊有限状态自动机-新mealy型模糊有限状态自动机被建立。 |
| 8. | However , because - bisimulation is not always an equivalence relation , such characterization in the usual style of hml does not always exist for - bisimulation associated with an arbitrary metric
但由于不为超度量时-互模拟一般不为等价关系,所以无法得到一个具有hml经典形式的逻辑特征。 |
| 9. | Secondly , it introduces the classical pawlak rough sets model , which is a uncertain and vague conception based on equivalence relation and expresses by upper and lower set approximations
接着介绍了经典( pawlak型)粗糙集模型的基本理论，它是建立在等价关系基础之上的，用上下近似集合来表示一个不精确的概念。 |
| 10. | A method based on fuzzy equivalence relation is applied to implement target classification and a synthetic algorithm is presented to fulfill multi - layer structure among groups by using the nearest - neighbor method and field knowledge
应用基于模糊等价关系的方法实现目标编群，并提出一种基于域知识和最近邻法相结合的算法来实现群结构递增形成的策略。 |
