this paper aims to assess the application of support vector machine (svm) regression in order to analysis flexible pavements. to this end, 10000 four-layer flexible pavement sections consisted of asphalt concrete layer, granular base layer, granular subbase layer, and subgrade soil were analyzed under the effect of standard axle loading using multi-layered elastic theory and pavement critical r...

a simple and rapid method for the determination of 137ba isotope abundances in water samples by inductively coupled plasma-optical emission spectrometry (icp-oes) coupled with least-squares support vector machine regression (ls-svm) is reported. by evaluation of emission lines of barium, it was found that the emission line at 493.408 nm provides the best results for the determination of 137ba a...

accurate forecasting of streamflows has been one of the most important issues as it plays a key role in allotment of water resources. river flow simulations to determine the future river flows are important and practical. given the importance of flow in the coming years, in this research three stations: haji qooshan, ghare shoor and tamar in gorganrood cachment were simulated in 2002-2011. to s...

A new robust version of Support Vector Machine (SVM) based on value-at-risk (VaR) measure referred to as VaR-SVM is proposed in three closely related formulations, and relationships between those VaRSVM formulations is established. In contrast to classical SVMs (hard-margin SVM, soft-margin SVM, and ν-SVM), VaR-SVM is stable to data outliers. Computational experiments confirm that compared to ν...

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...

In this paper, we show that the popular C-SVM, soft-margin support vector classifier is equivalent to minimization of Buffered Probability of Exceedance (bPOE) by introducing a new SVM formulation, called the EC-SVM, which is derived as a bPOE minimization problem. Since it is derived from a simple bPOE minimization problem, the EC-SVM is simple to interpret with a meaningful free parameter, op...

in this paper, we present a new brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (ls-svm). the method consists of three steps. in the first two steps, the skull is removed and cerebrospinal fluid (csf) is extracted. these two steps are performed using the fast toolbox (fmrib's a...

Learning ranking (or preference) functions has become an important data mining task in recent years, as various applications have been found in information retrieval. Among rank learning methods, ranking SVM has been favorably applied to various applications, e.g., optimizing search engines, improving data retrieval quality. In this paper, we first develop a 1-norm ranking SVM that is faster in...