Support vector machine (SVM) is a very popular method for binary data classification in data mining (machine learning). Since the objective function of the unconstrained SVM model is a non-smooth function, a lot of good optimal algorithms can’t be used to find the solution. In order to overcome this model’s non-smooth property, Lee and Mangasarian proposed smooth support vector machine (SSVM) i...

This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...

The slope stability analysis is routinely performed by engineers to estimate the stability of river training works, road embankments, embankment dams, excavations and retaining walls. This paper presents a new approach to build a model for the prediction of slope stability state. The support vector machine (SVM) is a new machine learning method based on statistical learning theory, which can so...

-The stock market is a very complex system, so it is necessary to use the support vector machine (SVM) algorithm with small sample learning characteristics. The stock market is also a chaotic system, whose financial time series data has chaotic characteristics of random, noise and strong nonlinear. However, the support vector machine for a given time series is usually not considered its chaotic...