Time series prediction techniques have been used in many real-world applications such as
financial market prediction, electric utility load forecasting, weather and environmental state …

The unique physicochemical properties, flexible structural tunability, and giant chemical
space of ionic liquids (ILs) provide them a great opportunity to match different target …

The defects retained during laser powder bed fusion determine the poor fatigue
performance and pronounced lifetime scatter of the fabricated metallic components. In this …

The hydrogen-enriched natural gas engines (HENGEs) have recently found huge popularity.
Despite the broad range of applications of the HENGE, their environmentally-associated …

Document-level sentiment classification aims to automate the task of classifying a textual
review, which is given on a single topic, as expressing a positive or negative sentiment. In …

In this paper we apply a recently proposed technique of optimal control by support vector
machines (SVMs) to chaos control. Vapnik's support vector method, which is based on the …

Least squares support vector machines (LS-SVM) is an SVM version which involves equality
instead of inequality constraints and works with a least squares cost function. In this way, the …

Although many methods are available to forecast short-term electricity load based on small
scale data sets, they may not be able to accommodate large data sets as electricity load data …

In this work, a framework based on the machine learning (ML) approach and Spearman's
rank correlation analysis is introduced as an effective instrument to solve the influence of …

Abstract In Support Vector Machines (SVMs), the solution of the classification problem is
characterized by a (convex) quadratic programming (QP) problem. In a modified version of …