提出一种属性值为区间灰数的不完备信息系统。
In this paper, the incomplete information system in which attributes values were considered as interval grey number.
同时，经典粗糙集理论缺乏对不完备信息的处理。
Simultaneously, the classical rough set theory is based on complete information systems.
首先，研究了在不完备信息系统下的属性约简算法。
Firstly, the attributes reduction algorithm is studied under the incomplete information systems.
提出了一种基于粗糙集的不完备信息系统数据填补方法。
This paper brought forward a data packing method of incomplete information system based on rough sets and grey system theory.
对如何直接从这种不完备信息表上找决策规则的方法也进行了讨论。
How to find decision rules directly from such an incomplete information decision table is also discussed.
在扩充粗糙集理论中，容差关系是一种处理不完备信息系统的工具。
Tolerance relation is an effective tool in patulous rough set theory to deal with incomplete information systems.
该算法无需改变初始不完备信息系统的结构，能直接处理缺省数据。
The algorithm could deal with incomplete data directly and do not required changing the size of the original incomplete system.
本文针对不完备信息系统属性约简的两种定义，证明了两者的等价性。
In this paper, the equivalence of two definitions of attributes reduction in incomplete information system is proved.
文中针对以上两个不足，提出了在联合行动和不完备信息下的协调学习。
In the paper, cooperated learning under joined action and imperfect information was proposed for solving these two problems.
定义了一种不完备信息系统的上、下近似算子，得到了一些相关的性质。
The upper approximation and the lower approximation operators are defined in incomplete information system. Furthermore, some related properties are discussed.
对一不完备信息系统进行了实例分析，以说明新提出的二元关系的有效性。
Analyzed an illustrative example to indicate the validity of the new-defined binary relation.
本文主要研究不完备信息系统下的知识获取方法，并取得了一些有意义的结果。
This thesis deals mainly with the knowledge acquisition methods as rough-sets, D-S evidence theory in incomplete information system, and obtains some significative result.
粗糙集理论是一种新颖、有效的软科学计算方法，能够分析和处理不完备信息。
Rough set theory has emerged as a major mathematical method to manage uncertainty which is from inexact, noisy and incomplete information.
通过实例，说明了基于修正容差关系的扩充粗糙集模型对处理不完备信息系统更加简便有效。
By an example, it is verified that the extension of rough set based on modified tolerance relation is more convenient and effective than the previous extensions in practice.
文中提出了一种基于绝对信息量的赋值规则，根据该规则提出了补齐不完备信息系统的算法。
This paper presents a rule based on the absolute information quantity. Then we provide an algorithm to make up an information system.
针对经典粗糙集模型只能处理完备信息系统，将变精度粗糙集模型引入到不完备信息系统中。
In view of the classical rough sets model can only dispose the complete information system, a variable precision rough sets model is introduced to dispose the incomplete information system.
通过实例，说明了基于修正容差关系的扩充粗糙集模型对处理不完备信息系统更加简便有效。
By an example, it is verified that the extension of rough set based on modified tolerance relation is more convenient and effective than the previous ex...
所以文章最后还给出了集值信息中的相似关系在处理不完备信息中的运用，并导出了它的递推公式。
Finally, the article also produced in the collection value information similar relations in the processing incomplete information utilization, and derived its recursion formula.
通过实例说明了这种方法是可行的，在一定程度上将粗集用于研究不完备信息系统方面进行了推广。
By an example, it is verified that this method is more feasible and rough set theory is extended in some way.
本文重点研究了在不完备信息系统中数据动态变化情况下的属性约简问题，针对已有算法提出了改进的算法。
This paper proposed an improved algorithms in incomplete information system data in the context of dynamic changes of attribute reduction for the existing algorithms.
其次，设计了一个基于本文提出的基于相容关系的分配约简遗传算法的高校人事不完备信息系统的知识获取模型。
Secondly, a knowledge acquisition model for the incomplete information systems for the university personnel system on the basis of the tolerance relation assignment reduction using GA is designed.
在此基础上结合粗糙集理论提出了相似矩阵、相似区间的概念，并将其应用于不完备信息系统知识分类的问题中。
On this bases, similar matrix and similar interval are proposed in combination with rough set theory. They are useful in knowledge partition problem in incomplete information system.
鉴于电力变压器信息的不完备性及复杂性，基于粗糙集理论提出了一种能较好处理不完备信息的变压器故障诊断模型。
Due to the incompleteness and complexity of fault diagnosis for power transformer, a specific fault diagnostic model with self-improvement method based on the Rough Set theory is given in this paper.
粗糙集理论作为一种处理不完备信息的有力工具，已广泛应用于人工智能的许多领域，特别是数据挖掘和知识发现领域。
Rough set theory, a powerful tool to deal with incomplete information, has been widely used in the area of artificial intelligence, especially in data mining and knowledge discovery.
粗糙集理论能有效地分析和处理不精确、不一致和不完整等各种不完备信息，并能从中发现隐含的知识，揭示潜在的规律。
The rough set theory can effectively analyze and deal with imprecise, incomplete, inconsistent and incomplete information, etc., and can find hidden knowledge, revealing the potential of knowledge.
本文研究了将两种常用于处理不完备信息的理论结合来给出一种新的相对约简算法，并给出实例计算结果，证明了算法的可行性。
This study proposes a new relative reduction algorithm by combing two theories which are frequently used to process incomplete information. It has been proved by example that the result is reliable.
对满足马尔可夫决策过程的服务组合提出了一种支持不完备信息描述的网格服务描述模型，实现了对服务组合整个生命周期的描述。
A new model based on Markov decision processes is proposed and the correlative novel algorithm is implemented with the adaptive ability of improved Q-learning for dynamic grid service selection.
应用这种方法能够将不完备系统转化为模糊信息系统，然后利用模糊粗糙集理论，让隐藏在不完备信息系统中的知识以决策规则的形式表示出来。
Based on fuzzy rough set theory, it is liable to change the incomplete system into fuzzy information system and make the covert knowledge stand out in a way of decision regularity.
股市的运行是一个非常复杂的不完备的非线性过程，因此，需要用对不完备信息进行处理的非线性模型代替传统的统计模型，以便进一步提高股市预测的质量。
As a result, it is necessary to replace the traditional statistic model with nonlinear model that can deal with imperfective information in order to improve the quality of forecasting stock market.
股市的运行是一个非常复杂的不完备的非线性过程，因此，需要用对不完备信息进行处理的非线性模型代替传统的统计模型，以便进一步提高股市预测的质量。
As a result, it is necessary to replace the traditional statistic model with nonlinear model that can deal with imperfective information in order to improve the quality of forecasting stock market.
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