This paper proposes a hybrid Bayesian Network (BN) method for short-term forecasting of crude oil prices. The method performed is a hybrid, based on both the aspects of classification of influencing factors as well as the regression of the out-of-sample values. For the sake of performance...

The aim of this project is to analyze high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, deceleration, and changes of direction from this high-frequency GPS location data. Time series of this...

We propose a coherent framework using support vector regression (SRV) for generating and ranking a set of high quality models for predicting emerging market sovereign credit spreads. Our framework adapts a global optimization algorithm employing an hv-block cross-validation metric, pertinent for...

The accurate forecasting of short-term load for urban gas is the premise of gas supply sales, pipe network planning, and energy optimization scheduling. This paper adopts a hybrid model that integrates the fruit fly optimization algorithm (FFOA), simulated annealing algorithm (SA), cross factor...

Housing prices in many countries have increased significantly over the past years, fueling a fear that speculative price bubbles will return. However, it can be difficult for policymakers to recognize when regulatory interventions in the market are necessary to counteract bubbles. This report...

„Wir glauben, der Siegeszug der digitalen Technik habe innerhalb weniger Jahre alles revolutioniert: unsere Beziehungen, unsere Arbeit, die Demokratie. Aber jetzt dreht der Soziologe Armin Nassehi den Spieß um und zeigt, dass es immer schon technische Revolutionen gab. Nicht die...