结果表明，径向基神经网络模型能有效提高预测精确度，也证明了实验方法的有效性和可行性。
The results not only show radial basis network models can increase the prediction accuracy efficiently, but also prove the validity and feasibility of these motheds.
试验结果表明，加入聚类分析的径向基神经网络模型提高了连续预测的趋势准确率，降低了时间代价，并减小了模型的复杂度。
The result of this experiment shows that the modified RBF neuro-network increases trend accuracy in sequential predicting, while debasing the cost of time and reducing the complexity of the model.
该文提出一个有效的基于径向基函数神经网络的模型和状态数据融合的汽轮发电机智能估计方法。
An efficient model based on radial basis function neural network and intelligent estimating method for data fusion of the turbine-generator is presented.
提出了一种隐马尔可夫模型（HMM）和径向基函数神经网络（RBF）相结合的语音识别新方法。
Presents a new hybrid framework of hidden Markov models (HMM) and radial basis function (RBF) neural networks for speech recognition.
研究了径向基函数(RBF)神经网络的模型结构及其在电力变压器故障诊断中的实现方法。
In this paper, the model structure and the application of Radial Basis Function Neural Network (RBF NN) to fault diagnosis of power transformer is presented.
径向基函数神经网络是一种拓扑结构简单、学习过程透明的神经网络模型。
Radial Basis Function Neural Network is a kind of Neural Networks which have simple topological structure and clear learn procedure.
采用径向基函数(RBF)神经网络方法进行能源消费量预测，建立了基于RBF神经网络的能源消费量预测模型。
Energy consumption prediction is made by the use of radial basis function (RBF) neural network method, and energy consumption prediction model based on RBF neural network is established.
提出了利用径向基函数神经网络进行水轮机综合特性曲线数据处理的方法，建立了相应的数学模型和约束条件。
The method for data processing of synthetic characteristics curve of hydraulic turbine is proposed, the corresponding mathematical model and the condition of constraint is established.
文中使用径向基函数理论建立了基于RBF神经网络的数控机床热误差数学模型。
A neural network based on radial basis function (RBF) was used to predict and compensate the thermal error of a CNC turning center.
提出了一种免疫聚类径向基函数神经网络(ICRBFNN)模型来预测电力系统短期负荷。
The paper presents an immune clustering RBF neural network (ICRBFNN) model for short-term load forecasting.
建立了基于相空间重构和径向基神经网络的压气机机匣静压的预测模型。
A novel forecasting model for compressor casing wall pressure based on phase space reconstruction and radial basis function network was established.
其次，根据损伤后的结构频率与模态的变化，应用径向基神经网络，进行结构节点固结系数的识别，从而实现对网架结构有限元模型的修正。
Secondly, according to the change of damage structural frequency and modal, the fixity factor is identified by RBF neural network, then FEM correction of truss is finished.
径向基函数神经网络模型的监测准确率高于其他两种模型，其平均验证误差为2.28%，最大验证误差低于10%。
For RBF neural network model, which is more effective to monitoring weld quality than the others, the average error validated is 2.28% and the maximal error validated is under 10%.
提出一种基于径向基函数(RBF)神经网络的模型跟随非线性自修复控制方法。
A new type of non linear self repairing control strategy based on model following method using radial basis function (RBF) neural networks is presented.
以径向基函数神经网络作为软测量模型，在软测量建模中引入正则化学习算法。
Using RBF (Radial Basis Function) network as the soft-sensing model, its natural to introduce regularization learning algorithm.
该算法中，径向基函数神经网络(RBFNN)用作前向模型，IGLSA用于求解逆问题中的优化问题。
In the algorithm, the radial-basis function neural network (RBFNN) is utilized as forward model, and the IGLSA is used to solve the optimization problem in the inverse problem.
以某水面舰艇为研究对象，利用径向基函数神经网络算法和标况下的水池实验数据，建立了基于航速、航向角和海情自适应变化的船舶横向运动非线性参数模型。
An intelligent model for a ship's horizontal motion, which can self-adapt with navigating speed, ocean condition and course, was established based on the Radial Basis Function (RBF) neural network.
研究基于聚类分析的径向基神经网络用于中医舌诊诊断，构建一个中医舌诊智能诊断的神经网络模型。
Presents the RBF neural networks based on clustering analysis is applied in TCM inspection of tongue diagnosis, to construct a neural networks model of TCM inspection of tongue intelligent diagnosis.
采用径向基神经网络（RBFNN）在MATLAB环境下建立了混煤软化温度的智能预测模型。
Through the use of a radial-based function neural network(RBFNN) an intelligent forecasting model for the blended-coal softening temperature was set up under MATLAB environment.
摘要 ： 提出了一种基于径向基函数（RBF）神经网络建立光电经纬仪等效跟踪误差模型的方法来评价光电经纬仪的跟踪性能。
Abstract : To effectively evaluate the tracking ability of a photoelectric theodolite, a new tracking error model based on the Radial Basis Function(RBF) neural network was established.
预测结果表明，径向基函数神经网络需水预测模型运算速度快，有较高的预测精度。
Abundant water demand predicting factors were used as the input data of the model, and the RBF neural network output the water demand predicting values.
在实际工业数据上进行的实验结果表明，支持向量机模型对丙酮纯度具有良好的预测效果，性能优于反向传播神经网络和径向基网络模型。
The experimental results on the real industrial data demonstrate that the model based on SVM achieves good performance and has less prediction errors than those of BPNN and RBFNN models.
提出一种优化径向基函数神经网络来波方位(DOA)估计模型结构和参数的方法。
A novel algorithm for optimizing the structure and parameters of Direction of Arrival (DOA) estimation model based on radial basis function neural network is presented.
在提出广义模糊推理概念的基础上，提出并分析了广义模糊径向基(rbf)神经网络模型，给出了该网络的广义学习算法。
A new concept of generalized fuzzy inference and the generalized fuzzy RBF network model are presented. The generalized Lear ni ng algorithm of this network model is derived.
用实际观测数据对该模型进行了试验，结果表明，用径向基神经网络转换GPS高程精度高于二次拟合法和BP神经网络法。
The model was tested with observed data. The results showed that RBF Neural Network conversion accuracy than Quadratic fitting and BP Neural Network.
用实际观测数据对该模型进行了试验，结果表明，用径向基神经网络转换GPS高程精度高于二次拟合法和BP神经网络法。
The model was tested with observed data. The results showed that RBF Neural Network conversion accuracy than Quadratic fitting and BP Neural Network.
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