[PDF] Top 20 A novel learning algorithm for data classification with radial basis function networks
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A novel learning algorithm for data classification with radial basis function networks
... One important advantage of the proposed learning algorithm, in comparison with the support vector machines, is that the proposed learning algorithm normally takes far less time[r] ... See full document
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A NOVEL LEARNINGALGORITHM FOR DATA CLASSIFICATION WITH RADIAL BASIS FUNCTION NETWORKS
... proposes a novel learning algorithm for constructing data classifiers with radial basis function (RBF) ...RBF networks constructed with ... See full document
6
Data Classification with Radial Basis Function Networks Based on a Novel Kernel Density Estimation Algorithm
... datasets with more than two classes of objects. In this paper, a novel learning algorithm is proposed for efficient construction of the RBF networks that can deliver the ... See full document
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An efficient learning algorithm for function approximation with radial basis function networks
... In this paper, an efficient learning algorithm for constructing function approximators with RBF networks is proposed. The proposed learning algorithm features a linear time [r] ... See full document
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Annealing Robust Radial Basis Function Networks for Modeling with Outliers
... initialization for robust learning ...occurs for nonlinear regression approaches in the statistics ...to a certain number beyond which a desired number cannot be ...criterion for ... See full document
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A Spatial Interpolation Method Based on Radial Basis Function Networks Incorporating a Semivariogram Model
... neural networks can automatically develop a forecasting model through a simple process of the historic ...Such a training process enables the neural system to capture the complex and nonlinear ... See full document
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Higher-Order-Statistics-Based Radial Basis Function Networks for Signal Enhancement
... supervised learning algorithm is developed to adapt ...LMS algorithm can be effectively solved by using HOS-based learning ...HOS-based learning algorithm is stable and superior ... See full document
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M-estimator based Robust Radial Basis Function Neural Networks with Growing and Pruning Techniques
... RBF learning algorithm with growing and pruning techniques is introduced in this ...is a widely used robust statistics ...beyond a threshold, the M-estimator suppresses the response ... See full document
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A Non-linear Rainfall-runoff Model Using Radial Basis Function Network
... two learning algorithms, the hybrid-learning algorithm offers computational effi- ciency and convergence ...training data towards the ...hybrid-learning algorithm. The values of ... See full document
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Estuary water-stage forecasting by using radial basis function neural network
... The Radial basis function neural network (RBFNN) has been successfully applied to many tasks due to its powerful properties in classification and functional ...presents a novel ... See full document
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A novel radial basis function network classifier with centers set by hierarchical clustering
... to the dendrogram to derive target clusters. Each node in the clustering dendrogram corresponds to a cluster of data instances. A node in the dendrogram is identified as a target cluster[r] ... See full document
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Flood Forecasting Using Radial Basis Function Neural Networks
... Training a RBF NN occurs in two ...method for finding the characteristics of the RBFs is always of ...clustering algorithm, which minimizes the sum of squares error (SSE) between the inputs and ... See full document
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Auto-configuring radial basis function networks for chaotic time series and flood forecasting
... neural networks, one of the most widely used is the radial basis function neural (RBFN) ...tinuous function to any prescribed degree of accuracy by given sufficient size of the network ... See full document
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A fair scheduling algorithm with traffic classification for wireless networks
... proposed for wireless networks to guarantee fairness and delay ...incurred for real-time flows. To resolve this problem, we propose a traffic-dependent wireless fair queuing (TD-FQ) ... See full document
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Environment-adaptation mobile radio propagation prediction using radial basis function neural networks
... P A REA The propagation of radio waves in built-up areas has been found to be strongly influenced by the nature of the environ- ment, in particular the size and density of ...Generally, a qualitative ... See full document
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Radial Basis Function-Based Neural Network for Harmonics Detection
... By comparing with several commonly used methods, it is shown that the proposed solution procedure yields more accurate results and requires less sampled data for harmonics assessment.[r] ... See full document
1
MICK: A Meta-Learning Framework for Few-shot Relation Classification with Small Training Data
... relation classification seeks to classify incoming query instances after meeting only few support ...training with large amount of in-domain annotated ...of data available at training time. We ... See full document
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Enhancing Bowel Sounds by Using a Higher Order Statistics-Based Radial Basis Function Network
... proposed for enhancing noisy bowel sounds in this ...the learning criterion designed by using higher order cumulants can reduce the influence of additional noise on adapting weights ...sounds for ... See full document
6
A generalized version space learning algorithm for noisy and uncertain data
... the learning strategy of version space to manage noisy and uncertain training ...data. A new learning algorithm is proposed that consists of two main phases: searching and ...into ... See full document
1
A generalized version space learning algorithm for noisy and uncertain data
... 2 A G ENERALIZED V ERSION S PACE L EARNING S TRATEGY This section proposes a generalized version space learning algorithm that provides more functions than the original learning ... See full document
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