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Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
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 ...
Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network
(Institute of Electrical and Electronics Engineers (IEEE), 2011-10-01)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, a technique that is precise, reliable, and ...
A panel data approach to economic forecasting: the bias-corrected average forecast
(Escola de Pós-Graduação em Economia da FGV, 2007-01-01)
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data ...
Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
The ability of a multi-model seasonal forecasting ensemble to forecast the frequency of warm, cold and wet extremes
(Elsevier Science, 2015-09)
Dynamical models are now widely used to provide forecasts of above or below average seasonal mean temperatures and precipitation, with growing interest in their ability to forecast climate extremes on a seasonal time scale. ...
Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter
(2011-10-05)
This paper proposes a filter based on a general regression neural network and a moving average filter, for preprocessing half-hourly load data for short-term multinodal load forecasting, discussed in another paper. Tests ...
Spatial load forecasting using a demand propagation approach
(2011-05-31)
A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses ...