This work describes an award winning approach for solving the NN3 Forecasting Competition problem, focusing on the sound experimental validation of its main innovative feature. The NN3 forecasting task consisted of predicting 18 future values of 111 short monthly time series. The main feature of...

This paper provides detailed information about team Leustagos’ approach to the wind power forecasting track of GEFCom 2012. The task was to predict the hourly power generation at seven wind farms, 48 hours ahead. The problem was addressed by extracting time- and weather-related features, which...

We propose a simple way of predicting time series with recurring seasonal periods. Missing values of the time series are estimated and interpolated in a preprocessing step. We combine several forecasting methods by taking the weighted mean of forecasts that were generated with time-domain models...

Combination techniques and decomposition procedures have been applied to time series forecasting to enhance prediction accuracy and to facilitate the analysis of data respectively. However, the restrictive complexity of some combination techniques and the difficulties associated with the...

The application of quantitative techniques for the determination of credit worthiness, i.e., the credit scoring, is a major research field for bankers and academics as it can bring about significant savings to finance institutions whilst minimising their exposure to risk. In the current work,...

This paper describes an objective way of predicting the likelihood of major league baseball players being elected to the Hall of Fame by members of the Baseball Writers' Association of America. A radial basis function (RBF) network is used to build separate machine learning models for pitchers...

We present a training algorithm for multilayer perceptrons which relates to the technique of principal component analysis. The latter is performed with respect to a correlation matrix which is computed from the example inputs and their target outputs. For large networks the novel procedure...

In the recent years, by rapid growth of wind power generation in addition to its high penetration in power systems, the wind power prediction has been known as an important research issue. Wind power has a complicated dynamic for modeling and prediction. In this paper, different hybrid...