We propose the representation of data from finite element car crash simulations in a graph database to empower analysis approaches. The industrial perspective of this work is to narrow the gap between the uptake of modern ...

We introduce an approach for damage detection in gearboxes based on the analysis of sensor data with the multi-resolution dynamic mode decomposition (mrDMD). The application focus is the condition monitoring of wind turbine ...

We investigate for car and component crash tests the comparison of highly resolved experimental data with corresponding simulation data. Due to re- cent advances for optical measurement systems, one can nowadays obtain ...

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a ......

Diese Arbeit beschäftigt sich mit einem neuen Ansatz für das Klassifikationsproblem beim Maschinellen Lernen durch Funktionsrekonstruktion. Es basiert auf dem Zugang des Regularisierungsnetzwerks, aber im Gegensatz zu ...

Data searchability has been utilized for decades and is now a crucial ingredient of data reuse. However, data searchability in industrial engineering is essentially still at the level of individual text documents, while ...

An approach to solve finite time horizon suboptimal feedback control problems for partial differential equations is proposed by solving dynamic programming equations on adaptive sparse grids. A semi-discrete optimal control ...

We propose a new mathematical data analysis approach, which is based on the mathematical principle of symmetry, for the post-processing of bundles of finite element data from computer-aided engineering. Since all those ...

The statistics obtained from turbulent flow simulations are generally uncertain due to finite time averaging. The techniques available in the literature to accurately estimate these uncertainties typically only work in an ...

We present a machine learning approach using the sparse grid combination technique for the forecasting of intraday foreign exchange rates. The aim is to learn the impact of trading rules used by technical analysts just ......