Recurrent neural networks for time series forecasting: Current status and future directions
Abstract Recurrent Neural Networks (RNNs) have become competitive forecasting methods,
as most notably shown in the winning method of the recent M4 competition. However …
as most notably shown in the winning method of the recent M4 competition. However …
An overview and comparative analysis of recurrent neural networks for short term load forecasting
FM Bianchi, E Maiorino, MC Kampffmeyer… - ar** models for short-term load
forecasting (STLF). Previous studies along this line of research have focused pre-dominantly …
forecasting (STLF). Previous studies along this line of research have focused pre-dominantly …
Short–mid-term solar power prediction by using artificial neural networks
Solar irradiation is one of the major renewable energy sources and technologies related
with this source have reached to high level applications. Prediction of solar irradiation shows …
with this source have reached to high level applications. Prediction of solar irradiation shows …
Towards short term electricity load forecasting using improved support vector machine and extreme learning machine
Forecasting the electricity load provides its future trends, consumption patterns and its
usage. There is no proper strategy to monitor the energy consumption and generation; and …
usage. There is no proper strategy to monitor the energy consumption and generation; and …
Hybrid PSO–SVM method for short-term load forecasting during periods with significant temperature variations in city of Burbank
A Selakov, D Cvijetinović, L Milović, S Mellon… - Applied Soft …, 2014 - Elsevier
This paper proposes a practical new hybrid model for short term electrical load forecasting
based on particle swarm optimization (PSO) and support vector machines (SVM). Proposed …
based on particle swarm optimization (PSO) and support vector machines (SVM). Proposed …