This paper investigates the application of neural basis expansion analysis with exogenous variables (NBEATSx) in the prediction of daily stock realized volatility for various time steps. It compares NBEATSx’s forecasting accuracy and robustness with several commonly used models, namely Long-Short Term …

This paper introduces and examines a novel realized volatility forecasting model that makes use of Long Short-Term Memory (LSTM) neural networks and the risk metric financial turbulence (FT). The proposed model is compared to five alternative models, of which two incorporate LSTM neural networks and …

Machine learning models have proven to be reliable methods in classification tasks. However, little research has been conducted on the classification of dwelling characteristics based on smart meter and weather data before. Gaining insights into dwelling characteristics, which comprise of the type of …

Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of …

Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of …

Currently, in a fast-growing electronic age, digital presence is becoming a necessity in order to maintain pace with the current technological evolution. In addition, increasing labor costs due to governmental regulations is challenging McDonalds’ scheme of providing low priced meals. Resorting to technology …

A considerable amount of literature has been published on Corporate Reputation, Branding and Brand Image. These studies are extensive and focus particularly on questionnaires and statistical analysis. Although extensive research has been carried out, no single study was found which attempted to predict …

The main objective of this study was to influence implicit learning through two different classical manipulations and to inspect whether working memory capacity (WMC) and personality were related to the different measures of learning. With that purpose, in Experiment 1 we asked 172 undergraduate students …

Tijdens het onderzoek is een oplossing gezocht waarmee tekst geclassificeerd kan worden. Dit met het doel informatie uit teksten te halen. Hiervoor is gezocht naar een machine learning oplossing binnen het vakgebied van Natural Language Processing (NLP). Deelvraag 1 Voor de eerste deelvraag is deskresearch …

Mixing examples of different categories (interleaving) has been shown to promote inductive learning as compared with presenting examples of the same category together (massing). In three studies, we tested whether the advantage of interleaving is exclusively due to the mixing of examples from different …