对径向基函数神经网络在数据分类中的应用进行了研究。
The application of radial basic function neural network in the data classification is studied.
提出一种交替梯度算法，对径向基函数(RBF)神经网络的训练进行改进。
One kind of alternant gradient algorithm for improving the training of Radial Basis Function (RBF) neural network is proposed.
提出了一种交替梯度算法对径向基函数(RBF)神经网络的训练方法进行改进，并将之运用于电力系统短期负荷预测。
This paper proposes one kind of alternant gradient algorithm for improving the training of RBF neural network, which is applied to short-term electric load.
并对该特征向量进行对数归一化，将归一化的特征向量作为径向基函数（RBF）神经网络的输入，在此基础上进行识别，达到较好的识别效果。
The normalized vector is used as the input of RBF NN, and target recognition is performed based on this, which leads to a satisfactory recognition result.
本文采用径向基函数(RBF)神经网络对货运量进行分析及预测。
The radial basis function (RBF) neural network is adopted to analyze and predict freight volumes.
该方法通过选择径向基函数中心、确定神经网络隐层神经元的数目和调整每一层的权值和阈值，对由于PSD非线性产生的误差进行修正。
The nonlinear error of PSD was modified by choosing the centre of RBF, ascertaining the number of neural cell of the neural network and adjusting the weight and the threshold of each hiberarchy.
针对PSD非线性对激光测平仪测量范围和测量精度的影响，采用一种新方法——径向基函数神经网络算法。
To eliminate the influence of nonlinear error of PSD on the measurement scale and accuracy of laser leveling tester, a new method of Radical Basis Function (RBF) neural network was used.
以某汽车为例，采用径向基函数神经网络对后悬架的阻尼进行了优化。
The rare suspension damping parameters of a jeep were optimized with radial basis function neural network.
利用径向基函数神经网络和选择的特征值对缺陷进行分类。
Defects are classified by radial basis function (RBF) network and features selected.
利用径向基函数神经网络和选择的特征值对缺陷进行分类。
Defects are classified by radial basis function (RBF) network and features selected.
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