Existing methods for structure discovery in time series data construct interpretable, compositional kernels for Gaussian process regression models. While the learned Gaussian process model provides posterior mean and variance estimates, typically the structure is learned via a greedy optimization procedure. This restricts the space of possible solutions and leads to over-confident uncertainty e...

Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Most of the PSO studies are empirical, with only a few theoretical analyses that concentrate on understanding particle trajectories. This paper overviews current theoretical studies, and extend these studies to applications in mechatronic systems, such as identification, control gains and o...

The aim of this experimental research is to confirm the correctness proposed methodology for optimizing atmospheric gas burners. Also, burner was tested in actual conditions. object optimization a typical modern households (required heat output average ranges from 8 12 kW) which will be applied order optimize its design characteristics and performance obtain energy efficient an environmentally ...