Abstract Developing Big Data applications has become increasingly important in the last few
years. In fact, several organizations from different sectors depend increasingly on …

The Big Data revolution promises to transform how we live, work, and think by enabling
process optimization, empowering insight discovery and improving decision making. The …

The prevalence of mobile phones, the internet-of-things technology, and networks of
sensors has led to an enormous and ever increasing amount of data that are now more …

Banks take great care when dealing with customer loans to avoid any improper decisions
that can lead to loss of opportunity or financial losses. Regarding this, researchers have …

During the last few years there has been marked attention towards hybrid and ensemble
systems development, having proved their ability to be more accurate than single classifier …

The aim of this paper is to propose a new hybrid data mining model based on combination
of various feature selection and ensemble learning classification algorithms, in order to …

Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role
in optimizing energy scheduling and enabling more flexible and intelligent power grid …

In this digital era we are surrounded by social media applications and the hardware devices
(such as sensorsetc) which are pouring data at an astonishing rate. This incoming data from …

Purpose The purpose of this paper is to highlight the use of the big data technologies for
health and safety risks analytics in the power infrastructure domain with large data sets of …

In this study, we focus on semi-supervised data stream classification tasks. With the advent
of applications that generate vast streams of data, data stream mining algorithms are …