This paper provides an overview of the support vector machine (SVM) methodology and its
applicability to real‐world engineering problems. Specifically, the aim of this study is to …

Annual load forecasting is very important for the electric power industry. As influenced by
various factors, an annual load curve shows a non-linear characteristic, which demonstrates …

This paper presents an overview of feature-based (FB) methods developed for Automatic
classification of digital modulations. Only the most well-known features and classifiers are …

The real estate market has a close relationship with us. It plays a very important role in
economic development and people's fundamental needs. So, accurately forecasting the …

Diagnosis of potential faults concealed inside power transformers is the key of ensuring
stable electrical power supply to consumers. Support vector machine (SVM) is a new …

Soft sensors have been widely used in industrial processes over the past two decades
because they use easy-to-measure process variables to predict difficult-to-measure ones …

This paper presents the implementation of a new text document classification framework that
uses the Support Vector Machine (SVM) approach in the training phase and the Euclidean …

Although machine learning algorithms to predict the mechanical properties of concrete have
been studied extensively, most of the research focused on the prediction of the strength of …

Mixed-suspension mixed-product removal (MSMPR) crystallization process is critical for
optimal separation and purification operations in pharmaceutical and fine chemical …

In every organization, performing accurate risk assessment along with consideration of
increasing accidents is a necessary tool to prevent and reduce the fatal and non-fatal …