Short-term inflation forecasting: The M.E.T.A. approach

Short - Term Load Forecasting

This paper presents a novel hybrid method for short-term load forecasting. The system comprises of two artificial neural networks (ANN), assembled in a hierarchical order. The first ANN is a multilayer perceptron (MLP) which functions as integrated load predictor (ILP) for the forecasting day. The output of the ILP is then fed to another, more complex MLP, which acts as an hourly load predictor...

Short-Term Weather Forecasting

Short and Mid-Term Wind Power Plants Forecasting With ANN

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24...

Type-2 fuzzy logic approach for short-term traffic forecasting

The performance of many components in intelligent transportation systems depends heavily on the quality of short-term traffic forecasts. We propose a new method for forecasting traffic based on type-2 fuzzy logic. Type-2 fuzzy logic is powerful in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In our formulation, the value of a members...

Short and Mid-Term Wind Power Plants Forecasting With ANN

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24...