Such as the return of specific prediction method, smoothing index, grey model prediction, BP neural network, RBF neural network .
具体如回归预测法、指数平滑法、灰色模型预测法、BP神经网络法、RBF神经网络法。
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.
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。
A model of rough radial basis function (RBF) neural network with attribute significance is presented.
提出一种基于属性重要性的粗糙rbf神经网络模型。
Based on the idea of data parallelism, a parallel training model for RBF (radial basis function) neural network in time-series prediction to improve the training speed is proposed.
根据数据并行的思想，提出了在时序预测中并行训练神经网络的模型，以提高训练速度。
Then an end-point forecast model was built based on the RBF neural network by analyzing the melting technology and the RBF training algorithm.
然后通过对真空感应冶炼工艺机理的深入分析以及对神经网络算法的研究，建立了基于RBF神经网络的终点预报模型。
The paper presents an immune clustering RBF neural network (ICRBFNN) model for short-term load forecasting.
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。
On the basis of macroscopic dynamic traffic flow model which is frequently used in traffic control, Radial basis Function (RBF) neural network is designed.
根据常用的高速公路交通流宏观动态模型，建立了高速公路交通流的RBF神经网络模型。
A new model of lake and reservoir eutrophication assessment can be established with RBF network of artificial neural network.
运用人工神经网络中的RBF网络算法，建立一种新的湖库水质富营养化程度评价模型。
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.
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。
A prediction model of molten steel temperature based on RBF neural network was developed to reduce cost and improve temperature control accuracy for vacuum induction melting.
针对真空感应炉生产过程中温度测量成本较高及精度较差等不足，建立了基于RBF神经网络的真空感应炉终点钢水温度预报模型。
RBF neural network is a three-layer feedforward network and can be used to identify nonlinear model effectively.
RBF神经网络是一种三层前向网络，可有效用来进行非线性模型的辨识。
At last, this paper USES the RBF neural network that was optimized by the mentioned parallel model to predict the value of some nonlinear functions and the close of several stocks.
最后，本文应用上述并行模型优化的RBF神经网络对非线性函数值以及证券个股收盘价进行预测。
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%.
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%。
A new method was represented to model dynamic linear regression system driven by data, in which a bayesian network was combined with the RBF neural network.
结合贝叶斯网络和神经网络，提出了一种建立数据驱动型的动态线性回归系统模型的方法。
Simulation results indicate that the modeling method by using the RBF neural network identification technique is effective with the established model featuring a relative high precision.
仿真结果表明采用RBF神经网络辨识建模的方法是有效的，建立的模型精度较高。
One maneuvering target tracking method in which RBF neural network is applied to correct Kalman filter result in standard Interacting Multi Model (IMM) is proposed in this paper.
文中提出了一种应用rbf神经网络对标准IMM算法中的卡尔曼滤波结果进行校正的方法。
Lastly, the values of long-term dry shrinkage of crushed sand concrete were observed and predicted by using RBF neural network model.
最后，用R BF神经网络模型预测了石屑混凝土的长期干缩值。
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.
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。
The RBF neural network model has better convergence ability and impending speed than the BP neural network model.
RBF神经网络模型的收敛能力和逼近速度优于BP神经网络模型。
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.
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。
Based on BP and RBF neural network model, the dynamic error of experiment was modeled and forecasted.
基于BP、R BF神经网络模型对实验系统的动态误差进行建模和预测。
A flue temperature soft measurement model based on linear regression and RBF neural network was built to establish temperature feedback control.
基于线性回归和RBF神经网络构建火道软测量模型，为控制建立温度反馈环节。
This paper addressed the model of fire detector based on RBF neural network.
本文探讨运用RBF神经网络建立火灾探测器模型。
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。
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.
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。
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 control for speed limitation on freeway is a nonlinear and time variable system, it is difficult to model with a mathematical model. A control method based on RBF Neural Network is put forward.
针对高速公路限速控制是一个非线性时变系统、难以用数学模型准确建模这一特点，提出了R BF神经网络控制方法。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
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