In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …

With time, AI technologies have matured well and resonated in various domains of applied
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …

Groundwater resources (GWR) play a crucial role in agricultural crop production, daily life,
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …

Summary The use of Artificial Intelligence (AI) has increased since the middle of the 20th
century as seen in its application in a wide range of engineering and science problems. The …

In the recent few decades there has been very significant developments in the theoretical
understanding of Support vector machines (SVMs) as well as algorithmic strategies for …

There are many excellent toolkits which provide support for developing machine learning
software in Python, R, Matlab, and similar environments. Dlib-ml is an open source library …

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 …

Hyperspectral remote sensing technology has considerable research value in monitoring
and evaluating soil heavy metal pollution. In this study, the Three-River Source Region was …

Predicting student academic performance has long been an important research topic in
many academic disciplines. The present study is the first study that develops and compares …

In this paper we describe the algorithmic implementation of multiclass kernel-based vector
machines. Our starting point is a generalized notion of the margin to multiclass problems …