It has advantages in, RBF net approaching, classifying and learning.
网络在逼近能力、分类能力和学习速度上均有优势。
The structure and rational of RBF neural network are presented in detail.
详细地介绍了径向基神经网络的结构和基本原理。
In this paper, we put forward using RBF network to flatness pattern recognition.
本文提出了基于模糊距离的R BF网络板形缺陷模式识别法。
Then, the modified RBF nerve network is used to predict the load of gas pipeline.
再利用改进的RBF神经网络进行天然气管网负荷的预测。
The structure and features of radial basis function (RBF) network are introduced.
介绍了径向基函数(RBF)神经网络的结构和特点。
Through enough samples training, an effective RBF neural network can be established.
通过足够样本的训练，构造出一个有效的神经网络模型。
Through using RBF neural network, speech recognition of isolated words is carried on.
识别网络使用RBF神经网络，进行了孤立词语音识别。
The hidden-layer R of RBF neural network consists of a set of RBF (radial base function).
径向基函数（RBF）神经网络隐含层R由一组径向基函数构成。
A fuzzy controller for ship steering based on RBF networks and genetic algorithms is designed.
设计了一种基于RBF网络和遗传优化的船舶操纵模糊控制器。
It can train polynomial function, neural networks, or radial basis function (RBF) classifiers.
它可以对多项式函数，神经网络，径向基函数进行训练。
RBF network on line recognition, single neuron PID control and control algorithm are introduced.
介绍了RBF网络在线辨识、单神经元PID控制器和控制算法。
Analysis the current RBF neural network at the same time do some improve work on its training algorithm.
对现有的RBF神经网络进行了分析，并对训练过程中使用的聚类算法进行了改进。
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。
An online identification algorithm was constructed using the least squares method and an RBF neuro network.
针对控制模型的特点，利用最小二乘法和RBF神经网络构造了二次辨识的在线辨识算法。
A new method of subtractive clustering RBF network for air condition breeze fan fault diagnosis is presented.
提出了一种减聚类径向基函数神经网络的纺织空调送风风机故障诊断方法。
Radial basis function (RBF) neural network is performed through linear combination of nonlinear basis function.
径向基函数(RBF)神经网络通过非线性基函数的线性组合执行。
The results indicate that the method is feasible and the prediction capability of ANFIS is superior to the RBF network.
结果表明，利用神经网络进行可靠度时序预测是可行的，并且ANFIS的预测能力要优于rbf。
The paper presented an idea of applying information fusion technology based on RBF network in fault diagnosis of gas sensor.
文章提出了将基于RBF网络的信息融合技术应用于瓦斯传感器故障诊断的思想。
The final system yields 60 million gallons per day, and has real potential to become a model for RBF systems around the world.
该系统完工后，每天可生产6千万加仑的水，同时可以给世界各国的污水处理系统作参考。
The vast majority of coverage has so far focused on the disadvantages of RBF. But this narrative only tells part of the story..
截止目前，“天生碧池脸”的大多数报道都集中火力在其种种劣势上。但这种叙述是片面的。
It makes a comparison of the performance differences of 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。
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。
It has important theoretical significance and application value how to find an effective learning algorithm of RBF neural networks.
如何找到一种更加行之有效的RBF神经网络学习算法具有重要的理论意义和应用价值。
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。
The comparison of different kernel functions for SVM shows that RBF kernel function is most suitable for recognition of grape disease.
不同分类核函数的相互比较分析表明，径向基核函数最适合于葡萄病害的分类识别。
Through the cyclic subspace regression (CSR) being applied to determine the weight of the RBF networks, the RBF-CSR model is produced.
将循环子空间回归（CSR）引入到RBF网络中，建立了RBF—CSR模型，并将它应用于实际化工过程。
The method of fundamental solutions (MFS) with radial basis functions (RBF) approximation was developed for general thermoelastic analysis.
采用基于基本解方法和径向基函数插值的无网格算法(MFS- RBF)分析了广义的热弹性问题。
Fault diagnosis model and learning rule of RBF ANN is studied. Fault diagnosis principle and step of RBF ANN based on rough sets theory is given.
研究了RBF神经网络故障诊断模型及学习规则，给出了基于粗糙集理论的RBF神经网络故障诊断原理和步骤。
Aimed at the problems of document automatic classification, a classification method is proposed based on fuzzy vector space model and RBF network.
针对文本自动分类问题，提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
Checked by the experiments, the improved RBF network has less hidden neural units than before, at the same time keep the accurate of RBF based classifier.
经实验证明，基于改进后的RBF网络具有更少的隐含神经元，但仍然保持了基于RBF网络分类器的准确率。
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