We give some properties of random fuzzy rough sets.
给出了随机模糊粗糙集的性质。
Some applications of the rough sets are also introduced.
对粗糙集的应用进行了论述。
Finally, the homomorphism issues on Rough sets are discussed.
最后，研究了粗糙集的同态问题。
We analyze the time complexity of algorithm and compare it with Rough sets based algorithm.
文章分析了算法的时间复杂度，并同粗糙集算法进行了对比。
Rough sets theory is a new mathematical tool to deal with problems on vagueness and uncertainty.
粗糙集理论是一种新的处理含糊和不确定性问题的数学工具。
A method of constructing knowledge based fuzzy perceptron based on rough sets theory is proposed.
提出了用粗糙集理论构造模糊多层感知器的方法。
The discretization of real value attributes is one of the most main problems in rough sets theory.
连续属性的离散化是粗糙集理论的主要问题之一。
There are some methods for data mining, and then Rough Sets methodology is one of important methods.
进行数据挖掘的方法有许多，而粗集方法便是其中的主要方法之一。
By comparing rough sets and random sets, we derive the relation between belief function and lower probability.
首先将粗糙集与随机集作了比较，并由此得出了信任函数与下概率的关系。
Rough sets theory is emerging as a powerful tool as inducing knowledge classification knowledge from database.
粗合集合理论现在已成为数据库知识分类的一种强有力的工具。
From the rough sets theory, this text discusses the relations between the granularity, resolution and entropy.
论文从传统粗集理论出发，讨论在粗集理论中粒度、分辨度与熵的关系。
The conception of variation fuzzy rough sets is proposed and their relevant properties and theorems are given.
提出了变异模糊粗集的概念，并给出了变异模糊粗集的相关性质和定理。
Rougness, rough entropy, fuzziness, and fuzzy entropy are major methods for measuring the uncertainty of rough sets.
粗糙集的不确定性度量方法，目前主要包括粗糙集的粗糙度、粗糙熵、模糊度和模糊熵。
For the future, realistic soft system based on this model of Rough Sets will be theoretically lucubrated and exploited.
今后的工作是开发基于这种粗糙集模型的实用软件系统和理论上的深入研究。
First we compare rough sets and random sets, and derive the relationship between belief function and lower probability.
首先将粗糙集与随机集作了比较，并由此得出了信任函数与下概率的关系。
To propose a modeling strategy of rolling horizon scheduling based on a rough sets theory and the general control idea.
提出了一种基于粗集理论和广义控制思想的滚动调度建模策略。
In this paper based on rough sets theory and neural network a new optimizing method of supplier 's choice is put forward.
本文提出了一种基于粗集理论与神经网络相结合的供应商优化选择新方法。
Herein, intelligence hybrid system based on rough sets and neural network for fault diagnosis is established in this paper.
并在此基础上构建了一个基于粗集一神经网络的智能混合故障诊断系统。
Rough sets theory was used widely to artificial intelligence, pattern recognition, data mining and knowledge discovery etc fields.
粗糙集理论被广泛应用于人工智能、模式识别、数据挖掘和知识发现等领域。
In this paper, the approximation operators and the random sets, the best parts of the rough sets theory, are studied systematically.
本文对粗糙集理论中最基本的部分——近似算子及随机集进行了较系统的探讨。
In this paper, the mathematical foundation study of rough sets and the study of two general rough sets models are mainly researched.
本文主要进行了粗糙集的数学基础研究，与程度粗糙集和变精度粗糙集两个广义粗糙集模型的探讨。
Objective: Correlative characteristic peaks of HPLC selected by rough sets were employed to identify the habitats of Radix Astragali.
目的：采用粗糙集方法选取相关特征色谱峰用于黄芪药材的产地鉴别。
As knowledge block in knowledge base is fuzzy and is obtained randomly, we study the rough set model based on random fuzzy rough sets.
当知识库中的知识模块既是模糊的又是随机得到的，我们定义了基于随机模糊集的粗糙集模型。
The effect extent of soil property for wheat yield was analyzed by using correlation analysis, grey associate analysis and rough sets theory.
运用简单相关、灰色关联分析方法和粗糙集理论，分析了土壤特性对小麦籽粒产量的影响。
In allusion to the redundancy of neural network structure, a optimizing method of neural network structure based on rough sets is established.
针对神经网络的结构存在冗余的问题，提出了一种利用粗糙集优化神经网络结构的方法。
In a sense, rough sets is a kind of self-study mechanism, so we can solve the problem of knowledge obtained automatically by using rough sets.
从某种意义上说，通过粗集理论挖掘出的分类规则是系统通过自学习机制而产生的，因而可以解决知识自动获取的瓶颈问题。
The basic topology, knowledge representation and inductive learning of an intelligent expert system on rough sets are introduced in this paper.
文章主要介绍基于粗集方法的智能专家系统的基本构成、知识表达方式及学习推理方法。
Fault diagnosis model and learning rule of RBF ANN is studied. Fault diagnosis principle and step of RBF ANN based on rough sets theory is given.
研究了RBF神经网络故障诊断模型及学习规则，给出了基于粗糙集理论的RBF神经网络故障诊断原理和步骤。
The main contents of the dissertation are as follows: the entropy methods to measure the uncertainty and the fuzziness in rough sets are proposed.
全文的主要内容如下：针对粗糙集中存在的不确定性和模糊性，提出了新的熵测量方法。
The System may adjust the control schemes by real time traffic data, which are off-line provided by the fuzzy traffic Decision table based on Rough Sets.
文章前面部分仿真分析通过的各种交通流情况下的基于粗集理论的模糊控制方案表在系统中离线给出，以根据实时的交通流数据查表调用。
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