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radial basis funetion(RBF) 径向基函数
Among them, the Radial Basis Function( RBF) neural network is a better model. 在这些预测模型中性能比较突出的是径向基函数网络(RBF)法。
The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel. 首先，用具有RBF核函数的LS-SVM离线建立被控物件的非线性模型；
In this work, MLP is substituted by a radial basis function (RBF) network, which solves these problems successfully. 通过引入径向基函数(RBF)网络替代多层感知器网络，较好地克服了这些缺点。
Radial Basis Function(RBF) ANN using Dempster-Shafer theory of evidence which is abbreviated evidence network is presented to diagnose analog circuits. 本文探讨了RBF神经网络结合D-S证据理论的D-S证据神经网络在模拟电路故障诊断上的应用。
A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure. 在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数,使网络结构得到优化。
In this paper, genetic algorithm was applied in the training of radial basis function (RBF)to establish a fault diagnosis network, which was used in bearing diagnosis. 将演化计算方法引入径向基函数(RBF)网络的训练过程，建立一个故障诊断模型，并给出学习训练算法。最后，将其应用于轴承的故障诊断中。
An identification algorithm for vibrating dynamic characterization by using RBF (radial basis function) artificial neural network is developed for multi-degree of freedom systems. 基于径向基函数(RBF)神经网络，提出了水轮机振动荷载参数识别方法。
The trained weights consist of cubic spline functions, not constants like the popular learning algorithm such as backpropagation (BP) or radial basis function (RBF) networks. 通过求解两组线性方程组，就可以确定具体三次样条权函数形式。
RBF(radial basis function) neural network model for analyzing the monitoring data of tailings dam was established,and then trained and tested using practically collected data. 建立了尾矿坝监测数据分析的RBF神经网络模型,并利用实际数据对此网络进行了训练和检验。
A raised-cosine function is used as the radial basis function in the RBF neural network.It has good ability to approximate multivariable nonlinear system. 该方法采用增量馀弦函数作为RBF网络的基函数，对多变数非线性系统有很好的拟合能力。
This method combines a genetic algorithm with an artificial neural network classifier, such as back-propagation( BP) neural classifier, radial basis function( RBF) classifier or learning vector quantization( LVQ) classifier. 此方法结合基因演算法与类神经分类器，如倒传递分类器、射基底函数分类器以及学习矢量量化分类器。
RBF(radial basis function) has the advantages of fast learning, not easily getting in the local minimum, so as to more attentions and more applications instead of BP learning algorithm. 径向基函数(radial basis function，简称RBF)神经网络作为人工神经网络的一种，以其牢固的插值理论为基础，并且具有学习速度快、不易陷入局部极小等优点，逐步取代反向传播(back propagation，简称BP)学习算法在模式识别领域中得到越来越广泛的关注和应用。
This method combines a genetic algorithm with an artificial neural network classifier, such as back-propagation (BP) neural classifier, radial basis function (RBF) classifier or learning vector quantization (LVQ) classifier. 此方法结合基因演算法与类神经分类器，如倒传递分类器、放射基底函数分类器以及学习矢量量化分类器。
Though similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. 在保留RBF3层网络结构基础上,EBF采用了最大期望算法来估计特征空间的混合密度分布参数,用椭球体集合来分解混合密度分布,从而构造了神经网络的中间层基函数的状态。
Though they are similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. 在保留 RBF三层网络结构基础上 ,EBF采用了 EM算法来估计特征空间的混合密度分布参数 ,用椭球体集合来分解混合密度分布 ,从而构造了神经网络的中间层基函数的状态。
We then investigate the suitable radial basis parameter used in DACE method. 然后我们研究了DACE里面基底函数的参数的适用性。
Average classification accura-cies indicated that the optimal kernel-parameter method could get optimal results, and was significantly better than that of Radial Basis Function (RBF) network. 分类结果表明，优化核参数的支持向量机分类器取得了最佳的分类效果，分类正确率明显高于径向基函数神经网络。
A generalized growing and pruning radial based function(RBF) neural network approach is used to estimate the battery's state of charge of the electric vehicles. 结合电池容量估计问题,将广义生长剪枝径向基函数神经网络方法用于判断电动车蓄电池的荷电状态。