• The method of fundamental solutions(MFS), one of the radial basis function(RBF) methods, employs the fundamental solutions to the governing differential operator as the Euclidean distance based RBF.

    基本解方法属于径向基函数类方法,它使用微分算子的基本解作为基于欧氏距离的径向基函数。

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  • 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。

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  • 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。

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  • A method based on radial basis function neural network (RBF) was presented, which could simplify data stream of automobile diagnosing instruments.

    提出了一种用r BF网络(径向基函数网络)简化汽车故障诊断仪数据流功能的方法。

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  • 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。

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  • A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure.

    在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数,使网络结构得到优化。

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  • 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。

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  • Due to its structural simplicity, the radial basis function (RBF) neural network has been widely used for approximation and classification.

    径向基函数(RBF)神经网络因其结构简单而被广泛地用于非线性函数近似和数据分类。

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  • Presents a new hybrid framework of hidden Markov models (HMM) and radial basis function (RBF) neural networks for speech recognition.

    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。

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  • A two-level learning method combining improved immune algorithm and least square method was proposed to design a radial basis function (RBF) network.

    结合改进的免疫算法和最小二乘法,提出了一种设计径向基函数(RBF)网络的两级学习方法。

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  • A cascade neural network composed of double-layer radial basis function (RBF) and linear basis function (LBF) is proposed for pattern classification.

    提出了由两层径基函数(RBF)和两层线性基本函数(LBF)网络组成的串联神经网络模式分类方法。

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  • One kind of alternant gradient algorithm for improving the training of Radial Basis Function (RBF) neural network is proposed.

    提出一种交替梯度算法,对径向基函数(RBF)神经网络的训练进行改进。

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  • A new method for processing output of surface roughness optical fibre sensor by radial basis function (RBF) neural network is presented in the paper.

    本文提出了以径向基函数(RBF)神经网络处理表面粗糙度光纤传感器输出信号的方法。

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  • The structure and principle of Radial Basis Function (RBF) neural network are studied.

    分析了径向基函数(RBF)网络的结构和工作原理。

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  • 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。

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  • 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。

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  • Lastly, the optimized proportional navigation of modern fighter is researched with radial basis function (RBF).

    最后,用径向基神经网络原理对载机导引器的优化作了研究。

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  • It mainly consists of a thick tin oxide gas sensor array and radial basis function(RBF) neural network.

    该电子鼻主要由一组厚膜金属氧化锡气体传感器阵列和RBF神经网络组成。

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  • 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。

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  • A new method for realizing the temperature compensation of capacitive pressure transducer based on radial basis function (RBF) neural network is proposed.

    提出了一种基于径向基函数(RBF)神经网络的电容式压力传感器温度补偿方法。

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  • The modelling problem of multivariable system using radial basis function (RBF) neural networks is studied.

    采用径向基函数(RBF)神经网络进行多变量系统的建模研究。

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  • Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.

    提出了一种基于免疫识别原理的径向基函数神经网络学习算法。

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  • For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.

    针对连续空间下的强化学习控制问题,提出了一种基于自组织模糊rbf网络的Q学习方法。

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  • 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。

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  • This paper introduces the radial basis function (RBF) network in the seismic data processing, and realizes the inserting data in seismic data processing with function approximation method.

    该文将径向基函数网络引入地震数据处理中,实现了函数逼近法地震数据的插值处理,在实际地震数据处理中取得了较好的应用效果。

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  • A neural network based on radial basis function (RBF) was used to predict and compensate the thermal error of a CNC turning center.

    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。

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  • The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel.

    首先,用具有RBF核函数的LS-SVM离线建立被控对象的非线性模型;

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  • The experimental data are used to train a radial basis function (RBF) artificial neural network, and the construction and parameters of the network are obtained for data fusion.

    实验数据被用来训练径向基函数(RBF)神经网络,得出的神经网络结构和参数用于数据融合。

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  • 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。

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  • 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。

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