The walk distances in graphs are defined as the result of appropriate transformations of the ∑∞ k=0(tA) k proximity measures, where A is the weighted adjacency matrix of a connected weighted graph and t is a sufficiently small positive parameter. The walk distances are graph-geodetic, moreover, they converge to the shortest path distance and to the so-called long walk distance as the parameter ...

Polyamide 6 / nitrile butadiene rubber / nanoclay (PA6/NBR/clay) nanocomposite has gathered wide acceptance in industry. Laser welding, as a fabrication method, is applied to welding of polymer nanocomposites. In this study, the input parameters (clay (Closite 30B) content, laser power, scan velocity and stand-off-distance) are varied to achieve the best responses (tensile strength of welds). R...

The intention of this paper is to show the applicability of a generalized conditional gradient method for the minimization of Tikhonov-type functionals, which occur in the regularization of nonlinear inverse problems with sparsity constraints. We consider functionals of Tikhonov type where the usual quadratic penalty term is replaced by the pth power of a weighted p-norm. First of all, we analy...

Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by local learning, we propose a method to speed up standard Gaussian process regression (GPR) with local GP models (LGP). The training data is partitioned in local regions, for each an individual GP model is trained. The...

In correspondence analysis, rows and columns of a data matrix are depicted as points in low-dimensional space. The row and column profiles are approximated by minimizing the so-called weighted chisquared distance between the original profiles and their approximations, see or example, Greenacre (1984). In this paper, we will study the inverse correspondence analysis problem, that is, the possibi...

Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by local learning, we propose a method to speed up standard Gaussian process regression (GPR) with local GP models (LGP). The training data is partitioned in local regions, for each an individual GP model is trained. The...

Wind power prediction is one of the most significant technologies to promote the capability of the whole power system that takes in wind electricity. A combined model for wind power forecasting is presented to decrease the influence of reconstructed parameters by chaotic time series analysis and the neural networks (NNs) in this work. The combined model respectively makes use of linear weighted...

introduction: as the statistical time series are in short period and the meteorological station are not distributed well in mountainous area determining of climatic criteria are complex. therefore, in recent years interpolation methods for establishment of continuous climatic data have been considered. continuous daily maximum temperature data are a key factor for climate-crop modeling which is...