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At the same time, linear regression, nonlinear regression and radial basis function (RBF) neural network models are set up to evaluate weld quality between the selected parameters and tensileshear strength.


For the RBF neural network model, which is more effective for monitoring weld quality than the others, the average error validated is 2.88% and the maximal error validated is under 10%.


To facilitate a valid control strategy design, this paper tries to avoid the internal complexities and presents a modelling study of SOFC performance by using a radial basis function (RBF) neural network based on a genetic algorithm (GA).


During the process of modelling, the GA aims to optimize the parameters of RBF neural networks and the optimum values are regarded as the initial values of the RBF neural network parameters.


Furthermore, it is possible to design an online controller of a SOFC stack based on this GARBF neural network identification model.

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During the process of modelling, the GA aims to optimize the parameters of RBF neural networks and the optimum values are regarded as the initial values of the RBF neural network parameters.


The validity and accuracy of modelling are tested by simulations, whose results reveal that it is feasible to establish the model of SOFC stack by using RBF neural networks identification based on the GA.


Optimization and characterization of electromagnetically coupled patch antennas using RBF neural networks


A practical method of estimation for the internalresistance of polymer electrolyte membrane fuel cell (PEMFC) stack was adopted based on radial basis function (RBF) neural networks.


This paper is concerned with the types of invariance exhibited by Radial Basis Function (RBF) neural networks when used for human face classification, and the generalisation abilities arising from this behaviour.

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Shape identification of electrocardiographic ST segment based on radial basis function neural network


In this paper, we introduce a computerized automatic identification method of the electrocardiographic ST segment shape with radial basis function neural network based on adaptive fuzzy system, which has a better effect than other methods.


Estimation of vegetation biophysical parameters by remote sensing using radial basis function neural network


The method of damage identification using the radial basis function neural network (RBFNN) is presented in this paper.


Fuzzy selfadaptive radial basis function neural networkbased control of a sevenlink redundant industrial manipulator

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A new algorithm using a RBF NN (radial basis function neural network) is proposed to predict this traffic chaos.


 其他 

 In this paper, we proposed the monitoring of chemical processes with a twostage RBF neural network The first stage is called the prediction network, which predicts the future state The second stage is called the fault diagnosis network, which checks the prediction result to identify whether there will be any faults and diagnoses the category of the faults identified In this way the monitoring of the process can be completed To improve the performance of a RBF neural network, we gave out a theorem... In this paper, we proposed the monitoring of chemical processes with a twostage RBF neural network The first stage is called the prediction network, which predicts the future state The second stage is called the fault diagnosis network, which checks the prediction result to identify whether there will be any faults and diagnoses the category of the faults identified In this way the monitoring of the process can be completed To improve the performance of a RBF neural network, we gave out a theorem and a revisionary method about RBF interpreation Then we proposed the other two methods in this paper They are used to improve the output of the two RBF neural networks respectively, by which the sample numbers of the two networks can be grately reduced We used the twostage RBF neural network to the monitoring the simulation of start process of the debutanizing column in the hydrocracking fracnation section, which showed a great success  文章提出用二级ＲＢＦ神经网络来实现化工过程的动态监控。第一级ＲＢＦ神经网络称作预测网络，用于预测未来一段时间内的有关状态量。第二级ＲＢＦ神经网络称作诊断网络，它根据预测量判断它们是否相应于某种事故状态，如果是，则提示操作人员采取相应的措施。这样可起到防患于未然的作用。ＲＢＦ神经网络的基础是ＲＢＦ插值，文章提出了改进的ＲＢＦ插值方法。文章又提出了提前一个时间步进行预测以获得预测结果修正项的方法。另外，文章还提出对诊断网络输出结果进行变换使能合理反映事故可能性的方法。文章所述方法被用于加氢裂化脱丁烷塔开工过程的动态监控，取得了满意的结果。  In this paper, the mathematical model, structure and its main functions of a fault diagnosis simulating system for marine diesel engine are presented. And the trouble diagnosis approach, which based on RBF neural network, is introduced. The system is simple in construction and perfect in func tion. It is of a practical importance to develop the performance fault analysis system of marine diesel engine in ocean ship and to train marine engineers.  该文阐述了船舶柴油机故障诊断仿真系统的模型、结构与功能，着重介绍了基于ＲＢＦ神经网络故障诊断方法。本系统具有结构简单、功能齐全等优点，对开发实船柴油机故障诊断的辅助分析系统和培训轮机员熟悉处理故障有实际意义。  A threestage classification system of handwritten digits recognition is presented for the automatic analysis system in UK psychology test. After eliminating the printed digits, binarization and thinning, some structural features, including the points, lines and circles are extracted for the firststage classifier. In this stage, two steps are taken, viz. the coarse and the fine classification. Zoning statistical features and 10 oneversus the rest support vector machines are used in the secondstage classifier.... A threestage classification system of handwritten digits recognition is presented for the automatic analysis system in UK psychology test. After eliminating the printed digits, binarization and thinning, some structural features, including the points, lines and circles are extracted for the firststage classifier. In this stage, two steps are taken, viz. the coarse and the fine classification. Zoning statistical features and 10 oneversus the rest support vector machines are used in the secondstage classifier. RBF network is used as the thirdstage classifier, and the features extracted are stroke features, projection features and Fourier transform features. Experiments have shown the effectiveness of the method.  针对 UK心理测试自动分析系统的手写体数字识别问题 ,提出了结构特征和统计特征相组合的三级分类方案 .经过印刷体去除、二值化、作业量判别等预处理之后 ,一级分类器提取点、线、圆等结构特征并进行组合构造相应模板 ,然后采用粗细两阶段方案进行模板匹配 ;二级分类器提取区域模糊统计特征 ,构造了 10个一对多的SVM分类器 ;三级分类器提取投影特征、笔划特征、Fourier变换特征等 ,然后利用 RBF神经网络进行分类 .实验表明该方法合理有效 .   << 更多相关文摘 
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