System modelling of non-stationary drying processes

Modelling and simulating non-stationary arrival processes to facilitate analysis

This paper introduces a method to model and simulate non-stationary, non-renewal arrival processes that depends only on the analyst setting intuitive and easily controllable parameters. Thus, it is suitable for assessing the impact of non-stationary, non-exponential, and non-independent arrivals on simulated performance when they are suspected. A specific implementation of the method is also de...

Modelling spray drying processes for dairy products

NIZO food research (The Netherlands) has been working for the food industry, the dairy industry in particular, for over 50 years. During the past 15 years NIZO food research has put a lot of effort into developing predictive computer models for the food industry. Nowadays the main challenges in the production of powders are the development of specialities (having a high added value) and the red...

Predicting non-stationary processes

1 Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequences. Consider the question when one of the measures predicts the other, that is, when conditional probabilities converge (in a certain sense), if one of the measures is chosen to generate the sequence. This question may be considered a refinement of the problem of sequence prediction in its most...

Non - Stationary Bayesian Modelling and

Learning Non-stationary System Dynamics Online Using Gaussian Processes

Gaussian processes are a powerful non-parametric framework for solving various regression problems. In this paper, we address the task of learning a Gaussian process model of non-stationary system dynamics in an online fashion. We propose an extension to previous models that can appropriately handle outdated training samples by decreasing their influence onto the predictive distribution. The re...