Traditional time series methods offer models whose parameters remain constant over time. However, industrial supply and demand processes require timely decisions based on a dynamic reality. A change in configuration, turning ...

In recent years, many studies have emerged about regarding the topic of school failure, showing a growing interest in determining the multiple factors that may influence it [1]. Most of the researches that attempt to solve ...

Cancer is a constantly evolving disease, which affects a large number of people worldwide. Great efforts have been made at the research level for the development of tools based on data mining techniques that allow to detect ...

In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, ...

The concentration of police resources in conflict zones contributes to the reduction of crime in the region and the optimization of those resources. This paper presents the use of regression techniques to predict the number ...

One of the tasks of great interest within process mining is the discovery of business process models, which consists of using an event log as input and producing a business process model by analyzing the data contained in ...

The attribute selection is a very relevant activity of data preprocessing when discovering knowledge on databases. Its main objective is to eliminate irrelevant and/or redundant attributes to obtain computationally treatable ...