SVR model
LP SVR Model Selection Using an Inexact Globalized Quasi Newton Strategy
... An algorithm for LP-SVR model selection has been dis- cussed in this paper. We propose a quasi-Newton method for function minimization, that uses a globalization strategy and an inexact computation of first ...
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Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters
... the SVR to fit a function f (x), which may map multiple matching scores to a fused score to make the final decision of arbitrary one-to-one ...a SVR model, all input data with labels from arbi- trary ...
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A SVR Model for Differentiation of Syndromes in Traditional Mongolian Medicine
... In fact, most doctors of TMM mainly diagnose syndromes based on their experiences. It is necessary to research models of syndrome differentiation of Mongolian medicine. However, the models can rarely be found in ...
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Calibration of a Six-Port Position Sensor via Support Vector Regression
... function (γ), the tolerance of termination criterion (ε), the penalty parameter (C) and the constant ν. ν ∈ [0, 1] is the parameter that controls the number of support vectors. The optimal parameters of γ and C can be ...
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Multistep ahead River Flow Prediction using LS SVR at Daily Scale
... With respect to the number of parameters, LS-SVR is less complex than ANN. As discussed earlier, there are only three parameters in LS-SVR based approach, namely—regularization parameter ( ) RBF kernel ...
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Parameters Optimization Using Genetic Algorithms in Support Vector Regression for Sales Volume Forecasting
... The sales forecasting process is a critical one for most business. GA-SVR is applied to forecast the car sales volume in this study. In GA-SVR model, GA is used to select optimal parameters of ...
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Runway Incursion Event Forecast Model based on LS-SVR with Multi-kernel
... multi-kernel model is better than LS-SVR with individual kernel model and generalized regression neural network (GRNN) ...LS-SVR model is a proper alternative for forecasting of the ...
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Automatic generation of presentation slides for academic papers
... (SVR) model is employed to find out the importance of every sentence in an exceedingly paper, so integer linear programming (ILP) model is employed to pick out and align key phrases and sentences for ...
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Regional collaborative forecast of primary energy consumption in China, Japan and South Korea based on multi-source data combination
... learning model that can classify and regress. This model can introduce nonlinear classifiers for processing various types of input ...dimensions. SVR-based engineering applications have been widely ...
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Forecasting the Demand of Short Term Electric Power Load with Large Scale LP SVR
... The final analysis is in regard to the statistical proper- ties of the errors of the proposed LP-SVR model. Fig- ures 8 through 10 shows statistical plots known as “box plots.” These plots provide the ...
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PREDICT ARRIVAL TIME BY USING MACHINE LEARNING ALGORITHM TO PROMOTE UTILIZATION OF URBAN SMART BUS
... learning model that may provide more accurate ETA. SVR, which is based on the SVM classifier model, is chosen for this ...The SVR model developed in this paper has displayed good ...
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Support vector regression approach of modeling the superconducting transition temperature of borocarbide based superconductors
... [18]. SVR has a good sound mathematical framework that results in optimal solution for its optimization ...addition, SVR performs excellently by maintaining good generalization error when the input dataset ...
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Rainfall forecasting using Nonlinear SVM based on PSO
... forecasting model due to the use of a risk function consisting of the empirical error and a regularized term which is resulting from the structural risk ...effectual SVR model, SVR’s parameters must ...
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Dynamic Modeling of Biotechnical Process Based on Online Support Vector Machine
... At the beginning, Online SVR tries to check if the new sample can be inserted in the Remaining Set. This is the best case, because it is fast and does not increase the complexity of the machine. If this does not ...
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Increasing Hepatitis C treatment uptake among HIV-infected patients using an HIV primary care model
... care model also operates as one clinic session per week and is staffed by three HIV clinicians with Infectious Diseases certification, a psychiatrist, two clinical pharmacists specialized in HIV care, one health ...
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Identification of Treatment Efficacy-Related Host Factors in Chronic Hepatitis C by ProteinChip Serum Analysis
... the SVR group and eight were increased in the group of ...three SVR- increased serum proteins were identified as two Apo fragments and albumin, and among eight non–SVR-increased pro- teins, four ...
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Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA
... method, due to its outstanding properties such as simple geometric interpretation, reaching a general and unique solution is noticeable. Choosing best model in SVM model is equal to solving a quadratic ...
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Prediction of Transmitted Wave Height of Tandem Breakwater using Support Vector Regression
... physical model of tandem breakwater has been conducted by ...for SVR is taken from the experimental data of 108 data ...epsilon-SVR model is F/H i , B/d, X/d, H i /gT 2 and the output was H t ...
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EXPERIMENTAL DESIGN OF CAPACITANCE REQUIRED FOR SELF EXCITED INDUCTION GENERATOR
... firstly for the design of synchronization controllers. The modeling uncertainty of chaotic dynamics is adaptively learned on line by LS-SVR. One of the many merits of the proposed synchronization method is that ...
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An improved EEMD based hybrid approach for the short term forecasting of hog price in China
... FNN model is as follows: the number of hidden nodes varies from 3 to 12 and the optimum num- ber of hidden nodes that minimizes the error rate on the validation set is determined; the number of output nodes is set ...
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