Matthias Ihme

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A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters(More)
Many combustion models that are based on the flamelet paradigm employ a reaction progress variable. While such a progress variable is well defined for one-step reaction kinetics, this is typically not the case for complex chemical mechanisms. Consequently, several expressions for a progress variable have been utilized. In this paper a formal method for the(More)
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