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radial basis function machine

Heart Disease Diagnosis Based on Deep Radial Basis Function Kernel Machine

Heart Disease Diagnosis Based on Deep Radial Basis Function Kernel Machine

... years Radial Basis Function (RBF) Kernel Machines have been used in Machine Learning tasks, but there are certain flaws that prevent their usage in some up-to-date applications ...and ...

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Hybrid Machine Learning Model of Extreme Learning Machine Radial Basis Function for Breast Cancer Detection and Diagnosis: A Multilayer Fuzzy Expert System

Hybrid Machine Learning Model of Extreme Learning Machine Radial Basis Function for Breast Cancer Detection and Diagnosis: A Multilayer Fuzzy Expert System

... The use of data science and data mining in technology and machine learning has significantly contributed to medical science. In recent years, many studies have been done on early detection and prevention of ...

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Evolutionary extreme learning machine for the interval type-2 radial basis function neural network: A fuzzy modelling approach

Evolutionary extreme learning machine for the interval type-2 radial basis function neural network: A fuzzy modelling approach

... of function approximation and classification problems, FLSs of Interval Type-2 (IT2) have demonstrated to be more efficient to handle with uncertainties, such as nosiy and sparse data as well as their ability to ...

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Hybrid Machine Learning Model of Extreme Learning Machine Radial basis function for Breast Cancer Detection and Diagnosis; a Multilayer Fuzzy Expert System

Hybrid Machine Learning Model of Extreme Learning Machine Radial basis function for Breast Cancer Detection and Diagnosis; a Multilayer Fuzzy Expert System

... networks, Radial Basis Function (RBF), and single-layer feedforward models are a special state of this ...decision function that is ultimately learned in these three methods mentioned above is ...

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Radial Basis Function Neural Networks : A Review

Radial Basis Function Neural Networks : A Review

... Venkatesan and Anitha [66] have compared RBF neural network with multilayer perceptron network for diabetes diagnosis. Their results show that RBF network performs better than other models. Subashini et al. [67] have ...

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Writer Identification and Recognition Using Radial Basis Function

Writer Identification and Recognition Using Radial Basis Function

... transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a personal Digital Assistant (PDA), in postal addresses on envelopes, in amounts in back checks, in ...

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Face Recognition by Radial Basis Function Network (RBFN)

Face Recognition by Radial Basis Function Network (RBFN)

... using Radial Basis Function Network (RBFN) is an attractive solution for the researchers who are working on the field of machine recognition, pattern recognition and computer ...and ...

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Unified Noise Reduction using Adaptive Radial Basis Function

Unified Noise Reduction using Adaptive Radial Basis Function

... method of removing the speckle noise from SAR images with better performance by modifying the window size of Lee filter and then compressing by using wavelet transform. [15] Proposed an algorithm to restore noisy images ...

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Logic Programming In Radial Basis

Function Neural Networks

Logic Programming In Radial Basis Function Neural Networks

... Hebb (1949) developed the first learning rule, that is if two neurons are active in the same time, then the weight (the strength) between them should be increased. After that, many researchers (Rosenblatt, 1958; Minsky, ...

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Classifying ReachOut posts with a radial basis function SVM

Classifying ReachOut posts with a radial basis function SVM

... The entry from Thomson Reuters was planned to be a system in which an ensemble of base classi- fiers is followed by a final system combination step in order to provide a final answer. But this did not pan out, so we ...

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An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks

An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks

... Five data sets are selected from UCI Machine Learning Repository [15] to evaluate the performance of AL-RAN. Table 1 shows the information on the data sets. Al- though training and test data are separately ...

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Radial
      basis function neural network for software engineering measures  A
      survey

Radial basis function neural network for software engineering measures A survey

... Vector Machine) and RBFN to the issues of software measurement in order to increase the correctness as well as the ...(Radial Basis Function) and SVM has some secure relationship among them ...

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Compactly Supported Radial Basis Function Kernels

Compactly Supported Radial Basis Function Kernels

... Regularized least squares classification was suggested in Poggio and Girosi (1990) and inves- tigated in Rifkin et al. (2003). Recently the least squares support vector machine (LS-SVM) was used as a variant of ...

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A symmetric integrated radial basis function method for solving differential equations

A symmetric integrated radial basis function method for solving differential equations

... Numerical experiments indicate that IRBFs lead to matrices of higher condition numbers than DRBFs. For a smooth function, accurate approximations by the former may thus occur earlier as β increases. In this ...

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Training of Radial Basis Function Using Particle Swarm Optimization

Training of Radial Basis Function Using Particle Swarm Optimization

... a Radial Basis Function Network we need to specify the hidden unit activation function, the number of processing units, a criterion for modeling a given task and a training algorithm for ...

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Maximum 2-satisfiability in radial basis function neural network

Maximum 2-satisfiability in radial basis function neural network

... meaning function for feed- forward neural networks with three layers. Radial Basis Function (RBFNN) is a feedforward ANN that contains hidden layers which requires the calculation of centre ...

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Radial basis function neural network learning with modified backpropagation algorithm

Radial basis function neural network learning with modified backpropagation algorithm

... Several parameters in RBFNN trained with SBP (otherwise known as SBP- RBFNN) need to be considered. The activation function, number of nodes in all the three layers, the learning and momentum rates, bias, and ...

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Computing non-Newtonian fluid flow with radial basis function networks

Computing non-Newtonian fluid flow with radial basis function networks

... This paper reports a numerical method based on RBFNs for solving non-Newtonian fluid flow problems. The main advantages of the present method are its mesh-free nature and easy implementation. IRBFNs are employed to ...

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A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE

A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE

... the radial basis function partition of unity method (RBF-PUM) for solving the transport equation on the surface of the sphere and applied it to several benchmark problems from the ...

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Nonlinear Image Restoration Using a Radial Basis Function Network

Nonlinear Image Restoration Using a Radial Basis Function Network

... generalized radial basis function network (GRBFN) and a regu- larization ...blurring function itself, the existence of the in- verse of the blurring process does not need to be ...

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