Face expression recognition technology is one of the most recently developed fields in
machine learning and has profoundly helped its users through forensic, security, and …

Learning from a multi-class problem has not been an easy task for most of the classifiers,
because of multiple issues. In the complex multi-class scenarios, samples of different …

Ensemble methods with “perturb and combine” strategy have shown improved performance
in the classification problems. Recently, random forest algorithm was ranked one among …

Accurate power load forecasting has an important impact on power systems. In order to
improve the load forecasting accuracy, a new load forecasting model, VMD–CISSA–LSSVM …

Most of the classification approaches assume that the sample distribution among classes is
balanced. Still, such an assumption leads to biased performance over the majority class …

It is challenging to obtain accurate and efficient predictions in short-term load forecasting
(STLF) systems due to the complexity and nonlinearity of the electric load signals. To …

The rudder system is extensively used in aerospace, ships, missiles and other safety
demanding areas. Therefore, it is paramount to ensure that the performance of the system is …

The distribution of data has a significant impact on the results of classification. When the
distribution of one class is insignificant compared to the distribution of another class, data …

Nonuniform slot air bearing (NSAB) systems have two major advantages, the external air
supply and slot restrictor design, and their inherent multidirectional supporting forces and …

Spherical porous air bearing (SPAB) systems have been extensively used in various
mechanical engineering applications. SPABs are promising materials in high-rotational …