This paper describes an on-line method for building ε-insensitive support vector machines for regression as described in (Vapnik, 1995). The method is an extension of the method developed by (Cauwenberghs & Poggio, 2000) for building incremental support vector machines for classification. Machines obtained by using this approach are equivalent to the ones obtained by applying exact methods like...

in this work some quantitative structure activity relationship models were developed for prediction of three bioenvironmental parameters of 28 volatile organic compounds, which are used in assessing the behavior of pollutants in soil. these parameters are; half-life, non dimensional effective degradation rate constant and effective péclet number in two type of soil. the most effective descripto...

The regression depth method (RDM) proposed by Rousseeuw and Hubert [RH99] plays an important role in the area of robust regression for a continuous response variable. Christmann and Rousseeuw [CR01] showed that RDM is also useful for the case of binary regression. Vapnik’s convex risk minimization principle [Vap98] has a dominating role in statistical machine learning theory. Important special ...

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity mode...

background: water is considered as the main source of life but water resources are limited and nonrenewable. different factors have caused groundwater to decrease. therefore, modeling and predicting groundwater level is of great importance. methods: monthly groundwater level data of about 20 years (october 1991 to february 2012) from the hamadan-bahar plain, west of iran were used based on peiz...

various statistical methods have been proposed in terms of predicting the outcomes of facing special factors. in the classical approaches,  making the probability distribution or known probability density functions is ordinarily necessary to predict the desired outcome. however, most of the times enough information about the probability distribution of studied variables is not available to the ...

in this paper, a robust integral of the sign error (rise) feedback controller is designed for a rigid-link electrically driven (rled) robot manipulator actuated by direct current dc motor in presence of parametric uncertainties and additive disturbances. rise feedback with implicitly learning capability is a continuous control method based on the lyapunov stability analysis to compensate an add...

support vector machine (svm) was used to analyze the occurrence of roach in flemish stream basins (belgium). several habitat and physico?chemical variables were used as inputs for the model development. the biotic variable merely consisted of abundance data which was used for predicting presence/absence of roach. genetic algorithm (ga) was combined with svm in order to select the most important...