Manuel Schmitt

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Changes in land use and management have been strongly affecting mountain grassland, however, their effects on the net ecosystem exchange of CO(2) (NEE) and its components have not yet been well documented. We analysed chamber-based estimates of NEE, gross primary productivity (GPP), ecosystem respiration (R) and light use efficiency (LUE) of six mountain(More)
Particle swarm optimization (PSO) is a popular nature-inspired meta-heuristic for solving continuous optimization problems. Although this technique is widely used, up to now only some partial aspects of the method have been formally investigated. In particular, while it is well-studied how to let the swarm converge to a single point in the search space, no(More)
II.1. Introduction: The theoretical strong points of super-symmetry (SUSY) have motivated many searches for supersym-metric particles. Most of these have been guided by the MSSM and are based on the canonical missing-energy signature caused by the escape of the LSP's (`lightest supersymmetric particles'). More recently, other scenarios have received(More)
We study the frequently observed phenomenon of stagnation in the context of particle swarm optimization (PSO). We show that in certain situations the particle swarm is likely to move almost parallel to one of the axes, which may cause stagnation. We provide an experimentally supported explanation in terms of a potential of the swarm and are therefore able(More)
Imaging techniques are an excellent example for the continuous improvement of medical possibilities by technical innovation. One particularly relevant field of research is multimodal registration, where data sets must be aligned in order to make their structures overlay. The overlay of the image positions is reached by optimizing a similarity metric. A(More)
This paper investigates the frequently observed phenomenon of stagnation which appears on particle swarm optimization (PSO). We introduce a measure of significance of single dimensions and provide experimental and theoretical evidence that the classical PSO, even with swarm parameters known (from the literature) to be good, almost surely does not converge(More)
Particle Swarm Optimization (PSO) is a popular nature-inspired meta-heuristic for solving continuous optimization problems. Although this technique is widely used, the understanding of the mechanisms that make swarms so successful is still limited. We present the first substantial experimental investigation of the influence of the local attractor on the(More)
II.1. Introduction: The theoretical strong points of super-symmetry (SUSY) have motivated many searches for super-symmetric particles. Many of these have been based on the canonical missing-energy signature caused by the escape of weakly-interacting LSP's ('lightest supersymmetric particles'). Other scenarios also have been investigated, widening the range(More)
II.1. Introduction: The theoretical strong points of super-symmetry (SUSY) have motivated many searches for super-symmetric particles. Many of these have been based on the canonical missing-energy signature caused by the escape of weakly-interacting LSP's (`lightest supersymmetric particles'). Other scenarios have also been investigated, widening the range(More)