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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 ...
Predictive model for detecting customer’s purchasing behavior using data mining
(2019)
Profitability is one of the most important marketing objectives in a company, so estimating and detecting in advance what a customer will purchase from a defined product portfolio is an important factor. Considering that ...
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 ...