Neural Network Supervised Learning Unknown Function i x i y ˆ i y 1, 2 , i + + i e Neural Networks as Universal Approximators Feedforward neural networks with a single hidden layer of sigmoidal units are capable of approximating uniformly any continuous multivariate function, to any desired...
文档标题《Neural Computation Radial Basis Function Networks》,总页数为36页,主要介绍了与Neural Computation Radial Basis Function Networks相关的资料,希望对大家有用,欢迎大家浏览! 文档格式: .ppt 文档大小: 490.0K 文档页数: 36页 顶/踩数: 0/0
(1991)."UniversalApproximationUsingRadial-Basis-FunctionNetworks,"NeuralComputation,(1993)."ApproximationRadial-Basis-FunctionNetworks,"NeuralComputation,305-316.Statisticsvs.NeuralNetworksStatisticsNeuralNetworksmodelnetworkestimationlearningregressionsupervisedlearninginterpolationgeneralizationobservationstrainingsetparameters(...
This paper proposes a framework based on the cross-validation methods for constructing and training radial basis function (RBF) neural networks. The proposed growing RBF (GRBF) neural network begins with initial number of hidden units. In the process of training, the GRBF network adjusts the ...
1.A method of predicting surrounding rock displacement is set up by using the RBF nerve network s function of powerful nonlinear mapping and fast convergence rate, in which the monitoring data of surrounding rock displacement are chosen.选择现场监测的围岩位移数据为样本,利用径向基函数RBF神经网络具有...
A radial-basis function neural network model is developed to learn the mapping from quantifiable and nonquantifiable factors describing the work zone traffic control problem to the associated work zone capacity. This model exhibits good generalization properties from a small set of training data, a ...
Radial basis function(RBF) neural network was applied to determine soil types of hilly and mountainous terrains in Fengdu County of the Three Gorges region in China, the elevation in which ranges between 118.5m and 2000m, combining landsat enhanced thematic mapper plus (ETM+) data and topographic...
To forecast the freight volume more effectively,the authors analyzed the factors influencing freight volume and established an AHP model.Based on this model,a radial basis function neural network model for freight volume forecasting was presented.The historical statistical data from 1985 to 2004 were ...
rbf基函数径向functionradialbasis Radial Basis Function (RBF) Networks RBF network • This is becoming an increasingly popular neural network with diverse applications and is probably the main rival to the multi-layered perceptron • Much of the inspiration for RBF networks has come from traditional...
This is an experimental study to compare the performance of the widespread backpropagation network (BP) to the performance of a radial basis function (RBF) and a generalized regression neural network (GRNN) for potential use as on-line process models. Criteria for network comparison include general...