Predicting fatigue life of composite materials is essential to increase reliability of manufacturing systems. The predicting techniques for fatigue life of composite materials are not widely investigated. The support vector regression (SVR) is an emerging forecasting technique and has been...

In contemporary finance, derivatives such as futures and options have exerted increasingly prominent impact not only on risk management activities but also on price speculative activities. As a result of the high-leverage characteristic involved in derivative tradings, investors can gain...

Accurate tourist demand forecasting systems are essential in tourism planning, particularly in tourism-based countries. Artificial neural networks are attracting attention to forecast tourist arrivals due to their general nonlinear mapping capabilities. Unlike most conventional neural network...

Support vector machines (SVMs) have been successfully applied to solve nonlinear regression and times series problems. However, the application of SVMs for tourist forecasting has not been widely explored. Furthermore, most SVM models are applied for solving univariate forecasting problems....

Accurate employee turnover prediction plays an important role in providing early information for unanticipated turnover. A novel classification technique, support vector machines (SVMs), has been successfully employed in many fields to deal with classification problems. However, the application...