针对民用机场多因素气象预测问题的复杂性，该文构建出一种基于粗糙集的模糊神经网络模型。
For a multifactor weather prediction problem, this paper constructs a new model of fuzzy neural network based on rough set.
根据分层递阶的原则，提出一种将粗糙集理论与BP神经网络相结合的分类算法。
According to the hierarchical principle, a classification method is presented based on the combination of rough set theory and BP neural network.
详细介绍了数据挖掘技术的常用方法，包括模糊理论、粗糙集理论、云理论、证据理论、人工神经网络、遗传算法以及归纳学习。
Mostly used methods are introduced in detail, including fuzzy method, rough sets theory, cloud theory, evidence theory, artificial neural networks, genetic algorithms and induction learning.
本文的研究是从智能理论角度着手，把粗糙集理论与神经网络技术应用于我国上市公司财务预警的研究当中。
In this paper, begin with agent technology - rough set theory and ANN technology have been applied to research on financial risk.
基于粗糙集和神经网络的人脸识别方法是针对PC A方法中存在的高维数问题和它对未训练过的样本识别率低的缺点而提出的。
Face recognition based on rough set and neural network was proposed for the shortcoming of high dimension of PCA face recognition and low recognition rate for non-training samples.
提出了一种粗糙集理论与神经网络集成的风机故障诊断方法。
A new method of rough set and neural network for fan trouble diagnosis is presented.
研究粗糙集理论和BP神经网络算法，以及如何结合两者构建天然裂缝智能识别的应用。
Investigate the rough sets theory and BP neural network algorithm, and how to combine the two that for constructing a natural fractures intelligence identification application.
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 allusion to the redundancy of neural network structure, a optimizing method of neural network structure based on rough sets is established.
提出了使用粗糙集理论优化BP神经网络模型方法，并将优化后的网络模型应用于滚动轴承的故障诊断中。
This article proposes a usage of rough collection theory by optimizing the BP nerve network model method, and will apply the optimized network model in the rolling bearing breakdown diagnosis.
针对无指针式仪表表盘的数字识别问题，提出了一种基于特征提取和粗糙集特征约简的神经网络数字识别方法。
A neural network numeral recognition method based on feature extraction and rough set feature reduction is proposed for numeral recognition of non-pointer instrument dial.
结合粗糙集和模糊神经网络提出了一种粗糙模糊神经网络识别器的模型。
A model of rough fuzzy neural network classifier was presented by combining rough set and fuzzy neural network.
叙述了粗糙集-神经网络系统诊断电力电子电路的过程。
The diagnosing process of rough set-neural network system is introduced.
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。
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.
利用网络撕裂法逐层将复杂装备撕裂为较为简单的单元，并充分利用粗糙集和神经网络融合方法的优点进行故障诊断。
A fault diagnosis method is presented in this paper which is based on the rough neural network and network ripping and for the complex equipment.
设计了一种基于粗糙集——模糊神经网络技术的数据挖掘与数据融合集成系统。
One kind of integrated data mining and data fusion system's model is designed with fuzzy neural network based on rough sets.
为了快速诊断板级电路故障，提出了采用分类的粗糙集-神经网络-专家系统的混合系统实现雷达装备的故障诊断。
To diagnose the board-level circuit fault rapidly, we put forward a hybrid system of rough set, neural network, and expert system for fault diagnosis of radar equipment.
同时，粗糙集对于决策表噪声比较敏感，BP神经网络可以克服这个缺点。
In addition, rough sets is high sensitivity to the noise in the decision table, this weakness can be counterbalance by BP neural network.
利用粗糙集理论进行规则提取后，将规则结果融入神经网络中，从而构造了一种强耦合多层模糊粗糙神经网络。
After the rules were obtained based on rough set theory, the rules were embedded in the neural network, so that a kind of strong coupling multi-layer neural network was constructed.
它首先利用粗糙集理论对磨粒特征参数进行约简，这样能够大大减少了神经网络的输入维数。
At first, debris feature parameters are simplified based on rough sets theory, and the input information-dimensions is reduced.
利用粗糙集理论对原始数据进行约简，构建优化的粗糙集—神经网络智能系统。
The reduction of original data based on rough-set theory is derived and the optimized intelligent system with rough-set neural network is established in this paper.
并以实例对粗糙集-神经网络-专家系统的混合系统进行训练和实际诊断。
An example was trained and actually diagnosed with the hybrid system of rough set-neural network-expert system on this platform.
粗糙集理论和人工神经网络技术的特点都很鲜明并且有着较为明显的互补性。
The characteristics of Rough set theory and Artificial Neural Network are very bright and obviously complementary.
本文建立了基于模糊粗糙集的神经网络预测模型，对瓦斯涌出量进行了预测。
A novel artificial network model based on fuzzy-rough set for gas emission forecasting of coal is proposed in the paper.
提出了采用粗糙神经网络对膨胀土路基水毁灾害进行评价和预测的方法，并运用粗糙集理论确定了该神经网络的结构。
The method was presented to forecast the water-destroyed disaster of expansive soil roadbed by rough neural network. The structure of the neural network was confirmed by the rough set theory.
结合粗糙集理论和神经网络的各自特点，提出了一种基于粗糙集一神经网络的浮选过程药剂用量数学模型，并且与基于粗糙集控制思想的浮选过程药剂添加模型进行了比较。
A medicament dosage model of flotation process based on rough set theory and neural networks is proposed in this paper. It is compared with the medicament dosage model based on rough control theory.
然后，在上面内容的基础上，对粗糙集理论和神经网络进行融合的可行性进行了研究和论证；
Then, on the basis of the content above, explores and demonstrates the feasibility of the fusion of rough set and neural networks;
第四章尝试将粗糙集和神经网络应用于冷却塔的物料成本预估，探讨了基于粗糙集和神经网络的冷却塔的物料成本预估方法。
In chapter 4, the paper attempts to use rough set theory and Artificial Neural Network in the prediction of the material cost of the cooling tower.
第四章尝试将粗糙集和神经网络应用于冷却塔的物料成本预估，探讨了基于粗糙集和神经网络的冷却塔的物料成本预估方法。
In chapter 4, the paper attempts to use rough set theory and Artificial Neural Network in the prediction of the material cost of the cooling tower.
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