We propose a method based on finite mixture models for classifying a set of observations into number of different categories. In order to demonstrate the method, we show how the component densities for the mixture model can be derived by using the maximum entropy method in conjunction with conservation of Pythagorean means. Several examples of distributions belonging to the Pythagorean family a...

We present an optimization model to find joint inspection and maintenance policies for infrastructure facilities under performance model uncertainty. The objective in the formulation is to minimize the total expected social cost of managing facilities over a finite planning horizon. As in recent optimization models, performance model uncertainty is accounted for by representing facility deterio...

− A mixture probabilistic Principal Component Analysis (PCA) model is proposed as a multivariate process monitoring tool in this paper. High dimensional measurement data could be aggregated into some clusters based on the mixture distribution model, where the number of these clusters is automatically determined by the maximum likelihood estimation procedure. The multivariate statistical process...

rigorous mathematical modeling of adsorption processes in packed beds involves time-consuming computations which are considered as the fundamental weakness of such thorough mathematical models. thus, reducing the computation time was a key factor in improving adsorption mathematical models. in order to achieve this goal, an attempt was made to know how much using different numerical methods inf...