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提取规则
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  extracting rules
     A NEW METHOD EXTRACTING RULES FROM ARTIFICIAL NEURAL NETWORK AND ITS APPLICATION
     由神经网络提取规则的一种方法及其应用
短句来源
     It is a special case of fuzzy decision tree induction extracting rules from the data, which have symbol features and crisp classes.
     模糊决策树归纳是从具有模糊表示的示例中学习模糊规则的一种重要方法,从符号值属性类分明的数据中提取规则可视为模糊决策树归纳的一种特殊情况。 模糊决策树算法是清晰决策树算法的一种扩展。
短句来源
     Extracting rules from the data set with reduced attributes is actually a reduction computation of decision rules, which is usually based on heuristic algorithm.
     从属性约简后的数据集中提取规则实质上就是决策规则的约简计算,一般利用启发信息进行约简计算。
短句来源
     Extracting rules from ANN could be applied in the classification problems in data mining.
     从神经网络中提取规则可以有效地应用于数据挖掘中的分类问题。
短句来源
     Several methods of extracting rules from database using neural networks are surveyed in this paper:extracting rules based on BP network and BP algorithm using combining weight algorithm.
     评述了利用神经网络从数据库中进行规则发现的几种方法 ,采用权值组合算法提取规则 ;
短句来源
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  extracting rule
     Neural networks methods of extracting rule from database
     从数据库中提取规则的神经网络方法
短句来源
     The foundation on which this paper is built is the theory of domain ontology. By dint of the description method of objected information object,objected description of heterogeneous information as expressing form of information concept model,and the semantic relation of concept model is as internal contact of heterogeneous information extracting rule.
     本文在阐述了领域On-tology理论的基础上,借助于对象化信息对象的描述方法,以异构信息对象化描述为信息概念模型的表达形式,以概念模型的语义关系为异构信息提取规则的内在联系.
短句来源
     An expression method based on RDF(Resource Describe Frame) is built on WEB.By means of Ontology semantic logic relation,an extracting rule of heterogeneous information is proposed in heterogeneous information integration. Thus heterogeneous information can be processed automatically.
     在WEB上,建立了一种基于RDF异构信息语义的表达方式,借助ONTOLOGY语义逻辑关系,提出了在异构信息集成中一种异构信息的提取规则方法,来满足在异构信息集成中的异构信息的自动处理.
短句来源
  “提取规则”译为未确定词的双语例句
     Inductively Learn XPATH Web Information Extraction Rules
     归纳学习XPATH Web信息提取规则
短句来源
     The SVC and data description is used to analyze the sample data, and the obtained support vectors are used to get the association rules in this method.
     文中提出了一种基于支持向量机的关联规则提取方法,通过支持向量聚类、数据域描述等方法来归类样本数据,利用得到的支持向量来提取规则
短句来源
     Abstract preconditions and conclusions of a rule, and store them in two relational databases.
     提取规则的前提和结论部分,将它们存放于2个数据库中,采用两库关联的方式表达规则知识.
短句来源
     The evolutionary operations of OCEC do not act on rules, but on the given data directly.
     另外,OCEC的进化操作直接作用于数据而不是规则,进化结束后再从组织中提取规则
短句来源
     Rules Extraction from Prediction Models
     从预测模型中提取规则
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  extracting rules
Extracting Rules from Composite Neural Networks for Medical Diagnostic Problems
      
This paper presents FERNN, a fast method for extracting rules from trained neural networks without network retraining.
      
Much of the research on extracting rules from a large amount of data has focused on the extraction of a general rule that covers as many data as possible.
      
In the case that we aim at extracting rules for tolerant substitutions, y has the opposite meaning.
      
NEX provides the explanation for trained neural networks by extracting rules from the networks.
      
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This paper presents a fuzzy modeling method using fuzzy neural network With the back- propagation algo-rithm. The new method can identify the fuzzy model of a nonlinear system automaticlly. Fuzzy nenral networkis used to generate fuzzy rules and membership functions. The feasibility and inferential statistics of the methodis examined by using numerical data and XOR problem. As an experimental result,the FNN inproves accuracyand reliability,saves design time and minimizes system cost of fuzzy design.The FNN can...

This paper presents a fuzzy modeling method using fuzzy neural network With the back- propagation algo-rithm. The new method can identify the fuzzy model of a nonlinear system automaticlly. Fuzzy nenral networkis used to generate fuzzy rules and membership functions. The feasibility and inferential statistics of the methodis examined by using numerical data and XOR problem. As an experimental result,the FNN inproves accuracyand reliability,saves design time and minimizes system cost of fuzzy design.The FNN can be used for estimationof human injury in nuclear explosions and can be simplified to a rule neural network(RNN),which is used forpole extraction of signal.Preliminary simulation shows that FNN bas vast vistas in nuclear monitoring.(

本文实现了一种利用基于BP算法的模糊神经网络(FNN)建立模糊模型的方法。这种方法可自动生成非线性系统的模糊模型。FNN被用来产生模糊规则和隶属函数。用数值计算和异或(XOR)问题对该方法的可行性和置信度进行了检验。结果表明:模糊神经网络能显著地改进模糊系统设计中的准确度、可靠性、缩短设计周期、降低系统成本。FNN用于核爆对人员伤害估计并可将网络简化成一种用于信号极点提取的规则神经网络(RNN)。初步实验表明:在核监测领域有广泛的应用前景。

A new method is proposed for extracting general rules from an artificial neural network, which is trained by destructive learning. The method consistes of two phases of preprocessing and rule extracting. The preprocessing phase contains three parts:dynamic modification, cluster and pruning. The dynamic modification generates automatically or constructs a fully connected or non fully connected preliminary topological network having one hidden layer from initial rule set. Redundant and unimportant hidden unites...

A new method is proposed for extracting general rules from an artificial neural network, which is trained by destructive learning. The method consistes of two phases of preprocessing and rule extracting. The preprocessing phase contains three parts:dynamic modification, cluster and pruning. The dynamic modification generates automatically or constructs a fully connected or non fully connected preliminary topological network having one hidden layer from initial rule set. Redundant and unimportant hidden unites and links are deleted from a trained network respectively in the cluster and pruning phase, and then, the link weights remaining in the network are retrained to obtain the same MSE. Thus, we can obtain a simpler and smaller size network structure and extract a relatively small rule set by using pruned network. The method is applied to meteorologic cloud atlas data from AD reports of USA. Test results using test data set show the correctness and effectiveness of proposed method, and this method is a simple and feasible one.

提出一种由预处理和规则提取两阶段组成的方法从神经网络中提取规则.预处理阶段包含有动态修正、聚类和删枝3部分.动态修正是自动生成或由初始规则集构造出全联接或非全联接网络初步拓扑结构;聚类和删枝分别删截掉不重要或多余的隐含节点和联接,从而可以得到最简洁和规模小的拓扑结构,成为提取规则的基础.提出了规则提取算法并用于已删截好的网络提取规则.该方法应用于美国AD报告中气象云图的数据,提取出规则集,经过测试数据集的测试表明是正确的和有效的,并且是一种简单、可行的方法

In the process of metallurgical and chemical industry production, some control objects have complicated structures. It's difficult to express them with exact mathematical models and to control them with accurate control method. So at practice,this kind of object is usually controlled by the operators who have rich experience. In this paper, we proposed a semantic interval based approach to automatically generate the knowledge base of a fuzzy controller from the numerical data of the human operation for the interested...

In the process of metallurgical and chemical industry production, some control objects have complicated structures. It's difficult to express them with exact mathematical models and to control them with accurate control method. So at practice,this kind of object is usually controlled by the operators who have rich experience. In this paper, we proposed a semantic interval based approach to automatically generate the knowledge base of a fuzzy controller from the numerical data of the human operation for the interested system. The semifuzzy sets are used to express the experts' knowledge. The ID3 algorithm is used to generate the linguistic rule set of fuzzy controller. And using the neural network computation as the inference method, we get the exact output value. The results of the electric stove experiment show the applicability of the proposed semifuzzy approach for the design of a controller in real life cases.

针对生产中一些控制过程主要依靠有经验的操作工来完成,在实现其自动控制时,操作工的经验知识难以表达,提出以半模糊语义区间来表示经验知识,用ID3方法提取规则,用模式识别的方法对工况进行定性分类,用神经网络定量输出控制值.对加热炉的经验知识进行了提取,并设计出控制器,试验结果表明,本方法将模糊知识表达与神经网络相结合,具有很好的鲁棒性,并有自学习功能,使控制达到了预期的效果.

 
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