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动态rbf神经网络
相关语句
  dynamic rbf neural network
     Application of Dynamic RBF Neural Network in Modeling of Nonlinear System
     动态RBF神经网络在非线性系统建模中的应用
短句来源
     Single Neuron PID Control Based on Dynamic RBF Neural Network On-line Identification
     基于动态RBF神经网络在线辨识的单神经元PID控制
短句来源
     A dynamic RBF neural network algorithm used in pattern recognition
     一种用于模式识别的动态RBF神经网络算法
短句来源
     To complicated systems which are of characteristics of nonlinearity and time-variation in the industrial control fields, a self-adaptive single neuron PID control method was proposed based on the dynamic RBF neural network identification, which identified system model on-line by means of dynamic neural network identifier and acquired on-line tuning information of PID parameters, and the self-tuning of controller parameters was implemented by the single neuron controller, and the intelligence control of system was achieved.
     针对工业控制领域中复杂非线性时变系统,提出了基于动态RBF神经网络辨识的单神经元PID控制方法。 采用动态RBF神经网络辨识器在线辨识系统模型,获得PID参数在线调整信息,并由单神经元PID控制器完成控制器参数的在线自整定,实现系统的智能控制。
短句来源
  “动态rbf神经网络”译为未确定词的双语例句
     An Investigation Concerning the Prediction of Short-term Loads of Boilers based on a Dynamic RBF (Radical Based Function) Neural Network
     基于动态RBF神经网络的锅炉短期负荷预测研究
短句来源
     Simulation research on strip flatness and thickness control based on dynamic RBF neural networks
     基于动态RBF神经网络的板形板厚综合控制仿真研究
短句来源
     The hybrid model consists of two RBF neural networks. The former is a dynamic model with the leading phase,the behavior of which is similar to the feaure of piezoceramic actuator,but differs from the feature of piezoceramic in the aspect of their phase and magnitudes.
     混合模型由两个动态RBF神经网络构成,前者形成一个相位超前的动态模型,其特性与压电陶瓷的输出特性类似,但在相位和幅值上有所区别;
短句来源
     The RBFNN has the least nodes and high studying speed. A prediction model of MH-Ni battery is cited and simulated with the dynamic RBFNN. The ideal result is made, and a novel method is presented for prediction of MH-Ni battery capacity.
     所设计的神经网络具有最少的隐含层节点数,结构简单,提高了网络学习训练速度,基于动态RBF神经网络建立了MH-Ni电池容量预测模型,通过仿真,取得了理想的结果,为MH-Ni电池容量预测提供了新方法。
短句来源
     A estimation model of state-of charge (SOC) of MH-Ni battery is cited and simulated with the dynamic RBFNN. The ideal result is made, and a novel method is presented for estimation modeling of SOC of MH-Ni battery.
     基于动态RBF神经网络建立了MH-Ni电池荷电状态预估模型,通过仿真,取得了理想的结果,为MH-Ni电池荷电状态预估建模提供了新方法。
  相似匹配句对
     Qualitative Analysis of Dynamic Neural Networks
     动态神经网络的定性分析
短句来源
     Application of an Improved RBF Neural Network in the Prediction of Variation of Groundwater Level
     改进RBF神经网络在地下水动态预报中的应用
短句来源
     A Two-stage RBF Neural Network Used for the Dynamic Monitoring of Chemical Processes
     二级RBF神经网络用于化工过程的动态监控
短句来源
     Simulation and Prediction of Underground Water Dynamics based on RBF Neural Network
     基于RBF神经网络的地下水动态模拟与预测
短句来源
     Application of Dynamic RBF Neural Network in Modeling of Nonlinear System
     动态RBF神经网络在非线性系统建模中的应用
短句来源
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The temperature profile for a reverse flow reactor with catalytic combustion of air contaminated with volatile organic compounds (VOCS) varies with real time. In order to predict and control, a real-time prognosticate model of temperature profile for a reverse flow reactor was built based on dynamic RBF (Radial Basis Function) neural networks. An on-line correcting method of model parameters was proposed based on RBF networks?linear outputs, with special emphasis on constructing dynamic model. The simulation...

The temperature profile for a reverse flow reactor with catalytic combustion of air contaminated with volatile organic compounds (VOCS) varies with real time. In order to predict and control, a real-time prognosticate model of temperature profile for a reverse flow reactor was built based on dynamic RBF (Radial Basis Function) neural networks. An on-line correcting method of model parameters was proposed based on RBF networks?linear outputs, with special emphasis on constructing dynamic model. The simulation result has proved that the model presented in this paper is simple, highly accurate and can meet control demand.

清除工业废气中低浓度挥发性有机物(VOCS) 的流向变换催化燃烧反应器的床层温度依时变化,为了实现实时预测和控制,用动态RBF(Radial Basis Function)神经网络建立了反应器床层瞬态温度分布的预测模型。着重讨论了动态RBF神经网络的基本结构,依据RBF网络线性输出的特点,给出了预测模型参数的在线修正方法。仿真结果与中试装置现场数据的对照表明,所建立的模型简单、精度高,能满足控制要求。

The hybrid neural network dynamic hysteresis model, which consists of two dynamic neural networks in a cascade form,is proposed to approximate the hysteresis characteristics of piezoceramic actuator.The hybrid model consists of two RBF neural networks.The former is a dynamic model with the leading phase,the behavior of which is similar to the feaure of piezoceramic actuator,but differs from the feature of piezoceramic in the aspect of their phase and magnitudes.The latter is used to carry out the nonlinear transform...

The hybrid neural network dynamic hysteresis model, which consists of two dynamic neural networks in a cascade form,is proposed to approximate the hysteresis characteristics of piezoceramic actuator.The hybrid model consists of two RBF neural networks.The former is a dynamic model with the leading phase,the behavior of which is similar to the feaure of piezoceramic actuator,but differs from the feature of piezoceramic in the aspect of their phase and magnitudes.The latter is used to carry out the nonlinear transform of phase and magnitude for the approximation of output of piezoceramic actuator. Simulation and experiment on the piezoceramic actuator show that the proposed model to describe the behavior of piezoceramic actuator is effective.In comparison with PI model,the proposed model is of high precision.

提出了两个动态神经网络串联的混合神经网络动态迟滞模型,用以逼近压电陶瓷的迟滞特性.混合模型由两个动态RBF神经网络构成,前者形成一个相位超前的动态模型,其特性与压电陶瓷的输出特性类似,但在相位和幅值上有所区别;后者实现相位滞后的变换和幅值的非线性变换,以达到对压电陶瓷实际输出的逼近.仿真和实验表明,所提出的描述动态迟滞特性的动态迟滞模型是有效的.与PI模型相比较,具有较高的模型精度.*

The method of controlling the RBFNN data centers of the hidden layer is raised in this article based on the feature of the RBFNN. It is the dynamic nearest neighbor-Clustering Algorithm. This algorithm eliminates the factitious factor affecting the choice of data centers in existing algorithms. The RBFNN has the least nodes and high studying speed. A prediction model of MH-Ni battery is cited and simulated with the dynamic RBFNN. The ideal result is made, and a novel method is presented for prediction of MH-Ni...

The method of controlling the RBFNN data centers of the hidden layer is raised in this article based on the feature of the RBFNN. It is the dynamic nearest neighbor-Clustering Algorithm. This algorithm eliminates the factitious factor affecting the choice of data centers in existing algorithms. The RBFNN has the least nodes and high studying speed. A prediction model of MH-Ni battery is cited and simulated with the dynamic RBFNN. The ideal result is made, and a novel method is presented for prediction of MH-Ni battery capacity.

基于RBF神经网络的设计难点提出了一种动态确定隐含层节点数及数据中心的新方法,即动态最近邻聚类算法,消除了现有算法中人为因素对数据中心的影响。所设计的神经网络具有最少的隐含层节点数,结构简单,提高了网络学习训练速度,基于动态RBF神经网络建立了MH-Ni电池容量预测模型,通过仿真,取得了理想的结果,为MH-Ni电池容量预测提供了新方法。

 
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