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Forecast of operational data in electric energy plants using adaptive algorithm
(Corporación Universidad de la Costa, 2020)
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 ...
Indicators for smart cities: tax illicit analysis through data mining
(Corporación Universidad de la Costa, 2021)
The anomalies in the data coexist in the databases and in the non-traditional data that can be accessed and produced by a tax administration, whether these data are of internal or external origin. The analysis of certain ...
Algorithms for crime prediction in smart cities through data mining
(Corporación Universidad de la Costa, 2020)
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 ...
Classification and features selection method for obesity level prediction
(2021-06-15)
Obesity has become one of the world’s largest health issues, rich and poor countries, without exception, have
each year larger populations with this condition. Obesity and overweight are defined as abnormal or excessive
fat ...
Unsupervised learning algorithms applied to grouping problems
(Corporación Universidad de la Costa, 2020)
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 ...
Temporary variables for predicting electricity consumption through data mining
(Journal of Physics: Conference Series, 2020)
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, ...
Method based on data mining techniques for breast cancer recurrence analysis
(Corporación Universidad de la Costa, 2020)
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 ...
Selecting electrical billing attributes: big data preprocessing improvements
(Corporación Universidad de la Costa, 2020)
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 ...
Human activity recognition through wireless body sensor networks (WBSN) applying data mining techniques
(Springer Verlag, 2021-11-26)
The research field on technologies and wireless sensor networks (WSN) are becoming one of the most disruptive technologies that support different scenarios of ubiquitous and generalized computing. WSN applied to the human ...
Data mining applied in school dropout prediction
(Journal of Physics: Conference Series, 2020)
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 ...