Selecting the RBF Parameters using the Evidence
Selecting Evidence-Based Programs
... potential evidence - - based programs, based based programs, based upon priority risk behaviors and. upon priority risk behaviors and risk/protective factors:[r] ...
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Selecting GA Parameters for Intrusion Detection
... its parameters like population size, number of generations, mutation rate, crossover rate, selection type ...requires selecting appropriate percentage of attack samples in a data set to be able to find good ...
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The Runge phenomenon and spatially variable shape parameters in RBF interpolation
... 1], using spatially constant ε (solid lines) and spatially variable ε k (as described in the text; dashed lines) for (a) max norm error and (b) condition number for linear ...in RBF interpolation, as ε → 0, ...
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Automatically Selecting Parameters for Graph-Based Clustering
... data using a damped-window model, meaning that the weight of each individ- ual points decays exponentially over time according to a decay parameter λ , which makes the algorithm biased towards more recent ...
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Selecting Parameters of the Fuzzy Possibilistic Clustering Algorithm
... results using data sets are used and illustrate the simplicity and effectiveness of the proposed ...of parameters shows that a clustering algorithm with optimal values of fuzzy and typical exponents and a ...
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Selecting Parameters for Secure McEliece-based Cryptosystems
... 2 Preliminaries 2.1 Coding theory Error-correcting codes are widely used in practice, especially for information transfer over noisy channels. Applica- tions are: CDs/DVDs, DSL, DVB-TV, mobile phones, satellite ...
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Prediction of Rainfall Using MLP and RBF Networks
... Figure 2: Location map of the study area 4. R ESULTS AND D ISCUSSIONS Statistical software, namely, SPSS Neural Connection was used to train the network data with different combinations of parameters to determine ...
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Fast Gauss RBF Training Using Approximate Pole
... ploe RBF, Convex hulls, Large scale classification, ...Gauss RBF network has a large number of parameters is very powerful in machine learning ...Gauss RBF network for large data sets ...
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A Hybrid Framework using RBF and SVM for Direct Marketing
... by using the nonlinear kernels that maps the input space to a high dimensional feature ...the parameters that control the regression quality are the cost of error C, the width of tube and the mapping ...
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DisPredict: A Predictor of Disordered Protein Using Optimized RBF Kernel
... a RBF kernel and includes useful and advanced features for predicting disordered residues, called ...the parameters and thirdly, the novel features monogram (MG) and bigram (BG) assisted in determining an ...
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Ship Geometry Description Using Global 2D RBF Interpolation
... Original scientifi c paper Radial basis function (RBF) networks are the new, recently developed, meshless explicit, piecewise geometry description methods. Among many useful properties the RBFs have, they belong to ...
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Cubically convergent methods for selecting the regularization parameters in linear inverse problems
... Xie and Zou [20] improved the method studied in [14], proposed a new model function iterative method, and updated the model parameters in a computationally more stable manner. Also, in testing the Tikhonov ...
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Metrics for Developing Functional Requirements and Selecting Design Parameters in Axiomatic Design
... 4. Concluding remarks A number of concepts relating to the use of metrics in the process of developing a design solution axiomatically have been discussed. Some of these concepts might seem obvious, although all have ...
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Selecting Pedagogical Protocols Using SOM
... network using the data collected from the Felder tool. Most of the parameters of SOM network arise through an iterative process, where the network trains and the results are ...the parameters are ...
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Classification of Motor Imagery EEG Signals Using a CNN Architecture and a Meta-heuristic Optimization Algorithm for Selecting Training Parameters
... 2. Theoretical Background and Previous Works 2.1. EEG based Brain Computer Interfaces A BCI system based on EEG from MI signals consists usually of four fundamental stages, the first one concerns to the signal ...
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Using the correlation criterion to position and shape RBF units for incremental modelling
... proposed RBF network con- struction method. Gaussian RBF units were used in all the ...algorithmic parameters, P S , N G and ξ B , were set ...learning parameters of the ε-insensitive SVM al- ...
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Detecting Network Intrusion Using BPA & RBF Neural Network Algorithms
... Weight Updating Methods The neural network maps the input domainsonto output domains. The inputs are packet parameters and the outputs are classification of attacks information. The combination of input and output ...
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Multi Deployment of Dispersed Power Sources Using RBF Neural Network
... of selecting these data ranges is to match with the maximum load demand of the speci- fied system and also to implement a variety of DG sizes with a small step ...
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Selecting stimuli parameters for video quality studies based on perceptual similarity distances
... than using the mean of the dissimilarity scores, in order to account for variability in the use of the similarity ...acquisition parameters were held ...imaging parameters may not be monotonically ...
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Multilingual Speech Recognition Using Radial Basis Function (RBF) Neural Network
... 2.2 LPC Feature Extraction LPC analysis is considers as a strong Feature Extraction process of the input signal analysis to compute the main parameters of speech signals. LPC analysis consists of Pre- emphasis; ...
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