Many applications benefit from theory relevant to the identification of variables having large correlations or partial in high dimension. Recently there has been progress ultra-high dimensional setting when sample size $n$ is fixed an...

In this paper we present the application of techniques for Correlation Dimension Estimation to estimate the model order of electrical load data. Based on a correct model order, appropriately structured neural nets for load forecasting were designed. Satisfactory results were obtained in one-hour-ahead electrical load prediction on a six months benchmark from an electric utility in the USA.