ôbjectives: diagnosis of the psychiatric diseases is a bit challenging at the first interview due to this fact that qualitative criteria are not as accurate as quantitative ones. here, the objective is to classify schizophrenic patients from the healthy subject using a quantitative index elicited from their electroencephalogram (ëëg) signals. methods: ten right handed male patients with schizop...

An excavation damage zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. This paper presents an approach to build a model for the ...

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...