Application of Conditional Random Fields and Sparse Polynomial Chaos Expansions to Geotechnical Problems

In geotechnical applications, mechanical properties of soil vary spatially within the soil mass and they are often represented by random fields. When data at certain locations of the soil mass are available, conditional random fields may be used to incorporate them. In this paper, we combine conditional random fields with sparse polynomial chaos...

Stochastic Surrogates for Measurements and Computer Models of Fluids

Both measurements and computer simulations of fluids introduce a prediction problem. A Particle Image Velocimetry (PIV) measurement of a flow field results in a discrete grid of velocity vectors, from which we aim to predict the velocity field or related quantities. In Computational Fluid Dynamics (CFD), the output of the computer code depends...

Business Process Modelling for Measuring Quality

Business process modelling languages facilitate presentation, communication and analysis of business processes with different stakeholders. This paper proposes an approach that drives specification and measurement of quality requirements and in doing so relies on business process models as representations of business processes. The approach is...

MAIA: A framework for developing agent-based social simulations

Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty

There is increasing interest in long-term plans that can adapt to changing situations under conditions of deep uncertainty. We argue that a sustainable plan should not only achieve economic, environmental, and social objectives, but should be robust and able to be adapted over time to (unforeseen) future conditions. Large numbers of papers...

An environment to support flexible information modeling