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Mostrando ítems 11-20 de 1937
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 ...
Machine-learning techniques and short-term combination forecasting of industrial production
(2018)
The aim of this study was to develop short-term forecasts of the industrial production index in Brazil. Forecasts are made using five different methodologies: SARIMA, regressions, a structural, a dynamic factor models and ...
Forecasting and forecast-combining of quarterly earnings-per-share via genetic programming
(Universidad de Chile. Facultad de Economía y Negocios, 2008)
In this study we examine different methodologies to estimate
earnings. More specifically, we evaluate the viability of Genetic
Programming as both a forecasting model estimator and a forecastcombining
methodology. When ...
Top-down strategies based on adaptive fuzzy rule-based systems for daily time series forecasting
(Elsevier Science BvAmsterdamHolanda, 2011)
AFOR-TSM: A Tool for Forecast with Time Series Models
(Inst of Industrial Engineers; Cdr edition, 2012-01-01)
One of the most complex and necessary subjects in courses of Operations Management (OM) is that students understand and apply Time Series Models (TSM) to forecast future demand.