Quality assessment of heterogeneous surface radiation network data

assessment of the efficiency of s.p.g.c refineries using network dea

data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...

Linked Data Quality Assessment through Network Analysis

Linked Data is at its core about the setting of links between resources. Links provide enriched semantics, pointers to extra information and enable the merging of data sets. However, as the amount of Linked Data has grown, there has been the need to automate the creation of links and such automated approaches can create low-quality links or unsuitable network structures. In particular, it is di...

Study of Spatial Data Quality Elements and VGI Linear Data Quality Assessment Methods

Volunteered Geographic Information has provided a rich and valuable resource for spatial data in a variety of applications. Despite the many benefits, this information does not provide any guarantee for their quality. So far, there are several methods to determine the quality of VGI. In addition to introducing quality elements and their evaluation methods, the present study attempts to explore ...

Quality Assessment of 3d Building Data by 3d Surface Matching

This is a cooperative work between the Chair of Photogrammetry and Remote Sensing of ETH Zurich and the Research department of Ordnance Survey, called “Quality Assessment of 3D Building Data”. The project aims to derive methods to calculate metrics for the quantitative evaluation of 3D building models, which are assumed to be basic elements of a given 3D city model. The developed metrics should...

Representation of Adsorption Data for the Case of Energetically Heterogeneous Solid Surfaces Using Artificial Neural Network