At present, the excellent performance of support vector machine (SVM) has made it
successfully applied in many fields. However, when SVM is used for two-dimensional matrix …

Two main contributions of this paper are 1) the energy consumption of ships (ECS) in port is
predicted, 2) reduction strategies for energy consumption of ships in port are discussed by …

Usually the real-world (RW) datasets are imbalanced in nature, ie, there is a significant
difference between the number of negative and positive class samples in the datasets …

In this paper, a twin support vector machine (TWSVM) based on improved artificial fish
swarm algorithm (IAFSA) for fire flame recognition is proposed in view of the large …

Abstract Least Squares Twin Support Vector Machine (LST-SVM) has been shown to be an
efficient and fast algorithm for binary classification. In many real-world applications, samples …

Classification is the most basic and representative problem in data mining and machine
learning. In recent years, more and more evolutionary algorithms (EAs) have been used to …

Nowadays, the world witnesses an immense growth in Internet of things devices. Such
devices are found in smart homes, wearable devices, retail, health care, industry, and …

In the smart mariculture, batch testing of breeding traits is a key issue in the breeding of
improved fish varieties. The body length (BL), body width (BW) and body area (BA) features …

As an energizing direction in machine learning, multi-view learning (MVL) is aimed at
exploiting the information among different views for improving the generalization …

In the field of machine learning, collected data always have additional features which are
always referred as privileged information. Privileged information learning is mainly used to …