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SVR-FFS: A novel forward feature selection approach for high-frequency time series forecasting using support vector regression
(Elsevier, 2020)
n this paper, we propose a novel support vector regression (SVR) approach for time series analysis. An efficient forward feature selection strategy has been designed for dealing with high-frequency time series with multiple ...
Clean energies in Mexico: projections for solar energy
(Universidad La Salle México, Facultad de Negocios, 2021-06-13)
In this research we analyze the current situation and prospects for solar energy generation in Mexico in order to identify areas of opportunity for both investment for private initiative and intervention for public policies. ...
Applied LSTM neural network time series to forecast household energy consumption
(SCOPUS, 2021-07)
In Ecuador, energy consumption is accentuated in
the residential sector due to population growth and other
parameters, which leads to an increase in energy costs,
greenhouse gas emissions and fossil fuel subsidies. ...
On the forecasting of the challenging world future scenarios
(Elsevier Science IncNew YorkEUA, 2011)
Forecasting, integration, and storage of renewable energy generation in the Northeast of Brazil
(Escola Polit??cnicaPrograma de P??s-Gradua????o em Engenharia IndustrialUFBAbrasil, 2017-09-06)
FORECASTING OF PETROLEUM CONSUMPTION IN BRAZIL USING THE INTENSITY OF ENERGY TECHNIQUE
(Butterworth-heinemann LtdOxfordInglaterra, 1993)
Analysis of the integration of drift detection methods in learning algorithms for electrical consumption forecasting in smart buildings
(2022)
Buildings are currently among the largest consumers of electrical energy with considerable increases in CO2 emissions in recent years. Although there have been notable advances in energy efficiency, buildings still have ...
Fuzzy Prediction Interval Models for Forecasting Renewable Resources and Loads in Microgrids
(IEEE-Inst Electrical Electronics Engineers Inc, 2015)
Millennium Institute Complex Engineering Systems
ICM: P-05-004-F
CONICYT: FBO16
National Fund for Science and Technology
1140775
CONICYT/FONDAP/15110019
Noisy Chaotic time series forecast approximated by combining Reny's entropy with Energy associated to series method: Application to rainfall series
(IEEE Computer Society, 2017)
This article proposes that the combination of smoothing approach considering the entropic information provided by Renyi's method, has an acceptable performance in term of forecasting errors. The methodology of the proposed ...