Feature Selection in Wind Speed Forecasting using NARX Model

摘要

Wind speed forecasting is important for wind power generation and integration. In this study, Nonlinear Autoregressive model process with exogenous input (NARX) is proposed for wind speed forecast. The main aim of this experiment is to forecast wind speed with meteorological time series data as input variable using NARX model. Prior to forecasting ReliefF feature selection is used to identify important features for wind speed forecast and reduce the complexity of the model. Performance is evaluated in terms of mean square error when using the feature selection method with the NARX model.