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rbf neural network
    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
    Modelling of Graphitizing Furnace by Use of RBF Neural Network
    用RBF神经网络建立石墨化炉过程模型
    Predicting the Productivity of a Cold Rolling Sizing Unit by the RBF Neural Network
    用RBF神经网络预报冷轧精整机组的成材率
    By using a RBF neural network,the mapping extending between the eigenvector and fault modes can be established to realize a fault diagnosis,thus achieving a high diagnostic rate for such conditions as normal state,mass imbalance,rotor misalignment and foundation loosening fault of a centrifugal pump.
    应用RBF神经网络建立了从特征向量到故障模式之间的映射实现故障的诊断,对于离心泵的正常状态、质量不平衡、转子不对中和基础松动故障具有很高的诊断率。
    During the process of learning the RBF neural network,one can accelerate the converging process of learning by regulating the learning speed according to a performance function.
    在RBF神经网络的学习过程中,根据性能函数调节学习率,可以加快学习的收敛过程。
    To eliminate the influence of initial weights values of neural networks on controllers, a RBF neural network controller optimized by a new improved genetic algorithm (GA) is proposed.
    为了消除神经网络参数初值对控制器性能的影响,提出了一种改进遗传算法优化的RBF神经网络控制器。
    Based on the experimental data obtained from 71 steel plates rolled in 4200 rolling mill,this paper established a RBF neural network prediction model of influential coefficient in stressed state by Matlab neural network toolbox.
    以4200 mm轧机轧制71块钢板的实测数据为基础,利用Matlab人工神经网络工具箱,建立了轧制变形区的应力状态系数的RBF神经网络预测模型.
    The experiment and simulation show that the model of RBF neural network based on PCA has better effect than the common RBF neural network model,the construction of RBF network is simplified,and the precision is increased.
    仿真实验表明,基于PCA的RBF神经网络模型在拟合预测中与一般的RBF神经网络模型相比有较好效果,简化了网络结构,改善了预测精度.
    The learning algorithm of membership function based on the RBF Neural Network is discussed and an example is given to demonstrate the validity of this algorithm.
    文中探讨了一种用于提取模糊规则的RBF神经网络结构,提出了基于此网路结构的模糊隶属度函数学习算法,最后给出了用于验证该算法有效性的仿真实例.
    A new method of fire detection algorithm is proposed. By analyzing and comparing with BP neural network,the RBF neural network is much faster and more exact in data operation,so the algorithm and the technology has wider application better prospects in fire detection.
    提出了一种新的应用于火灾探测的算法,通过与BP神经网络算法的分析比较,认为RBF神经网络算法比BP神经网络算法在数据处理方面更加迅速和准确,因此RBF神经网络算法在火灾的实时探测方面具有更好的发展潜力,而基于RBF神经网络的气味分析技术在火灾探测方面表现出广阔的应用前景.
    According to the principle and character of the neural network ,elaborate the basic theories and advantages of the Fault Detection Diagnosis for Sensor using RBF neural network, put forward a kind of way of thinking and method used for fault detection diagnosis of High Molecule Humidity sensor based on RBF neural network.
    根据神经网络的原理与特点,阐述了基于RBF神经网络的传感器故障诊断的基本理论和优点,提出了一种基于RBF神经网络用于高分子湿度传感器进行故障诊断的方法。
    The thought of bacterial colony chemotaxis (BCC) algorithm is applied to determine the control parameters of the hidden neurons in RBF neural network.
    借用细菌群体趋药性(bacterial colony chemotaxis,BCC)算法的思想来确定RBF神经网络隐层神经元的控制参数;
    This paper gives a data fusion structure based on RBF neural network and D-S inference and its application in the fault diagnosis of bearing.
    提出一种基于RBF神经网络和D-S证据理论相结合的数据融合结构应用于轴承故障诊断。
    A solving plan of nonlinear filtering based on the RBF neural network is presented.
    提出了一种基于RBF神经网络的非线性滤波解决方案。
    It makes a comparison of the performance differences between the BP neural network and the RBF neural network in nonlinear filtering.
    比较了BP神经网络和RBF神经网络在非线性滤波中的性能差异。
    A adaptive learning algorithm of T-S fuzzy model based RBF neural network is proposed for the problems of enormous inference rules and difficult parameters identification in multi-dimension fuzzy inferences.
    针对多维模糊推理中的推理规则庞大和参数难辨识的问题,提出一种基于T-S模糊模型的RBF神经网络的自适应学习算法。
    (2) The RBF neural network model has better convergence ability and impending speed than the BP neural network model.
    (2)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.
    The feature level module adopts RBF neural network to extract feature of data and to make feature fusion.
    特征级融合模块采用RBF神经网络,其功能是提取数据特征进而特征信息融合。
    The Distributed RBF Neural Network and Its Application in Soft Sensor
    分布式RBF神经网络及其在软测量方面的应用
    Design of RBF Neural Network Control for Chaotic System
    混沌系统的RBF神经网络控制设计
 

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