Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

background: this paper proposes a new emotional stress assessment system using multi-modal bio-signals. electroencephalogram (eeg) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. methods: we design an efficient acquisition protocol to acquire the eeg signals in five channels (fp1, fp2, t3, t4 and pz) and peripheral signals such as blood volu...

estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. this estimation has a major impact on the success of construction projects. indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. the purpose of this paper is to introduce an intelligent model to im...

finding repetitive subsequences in genome is a challengeable problem in bioinformatics research area. a lot of approaches have been proposed to solve the problem, which could be divided to library base and de novo methods. the library base methods use predetermined repetitive genome’s subsequences, where library-less methods attempt to discover repetitive subsequences by analytical approaches. ...

In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...

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...