Firms use time-series forecasting methods to predict sales. However, it is still a question which method forecaster best, if only single forecast needed. This study investigates and evaluates different sales methods: multiplicative Holt-Winters (HW), additive HW, seasonal auto regressive integrated moving average (SARIMA) [a variant of (ARIMA)], long short-term memory (LSTM) recurrent neural ne...

The important problem of selecting the predictors in a high-dimensional case where number candidates is larger than sample size often solved by researchers from signal processing community using orthogonal matching pursuit algorithm or other greedy algorithms. In this work, we show how same can be applying methods based on concept stability. Even if it not new concept, stability less known comm...

The design and operation of modern energy systems are heavily influenced by time-dependent uncertain parameters, e.g., renewable electricity generation, load-demand, prices. These typically represented a set discrete realizations known as scenarios. A popular scenario generation approach uses deep generative models (DGM) that allow without prior assumptions about the data distribution. However,...