Abstract— This paper presents a novel support vector regression (SVR) network for financial time series prediction. The SVR network consists of two layers of SVR: transformation...
Recently, the Support Vector Regression (SVR) has been applied in the financial time series prediction. The financial data are usually highly noisy and contain outliers. Detecting ...
We propose a hybrid particle and texture based approach for the visualization of time-dependent vector fields. The underlying spacetime framework builds a dense vector field rep...
Daniel Weiskopf, Frederik Schramm, Gordon Erlebach...
We present a novel approach for the direct computation of integral surfaces in general vector fields. As opposed to previous work, which we analyze in detail, our approach is based...
Christoph Garth, Hari Krishnan, Xavier Tricoche,...
Topological methods aim at the segmentation of a vector field into areas of different flow behavior. For 2D time-dependent vector fields, two such segmentations are possible: eith...