Weighted means and weighting functions

DISA SEMINARI Generalizations of weighted means and OWA operators: an analysis and new proposals

Weighted means and ordered weighted averaging (OWA) operators are well-known functions widely used in aggregation processes. Although both are defined through weighting vectors, their behavior is quite different: The weighted means allow to weight each information source in relation to their reliability while OWA operators allow to weight the values according to their ordering. Nevertheless, th...

Weighted Quasi-Arithmetic Means: Utility Functions and Weighting Functions

Weighted L2 Cohomology of Asymptotically Hyperbolic Manifolds

The main results are summarized by Figure 1. They demonstrate the resiliency of the isomorphism constructed in [Nai99] between weighted cohomology and a variant of weighted L2 cohomology. Our attention is restricted from generic locally symmetric spaces to spaces whose ends are hyperbolic, diffeomorphic to (0,∞) × (S1)n−1, and carry exponentially warped product metrics. For weighting functions ...

Weighted Ensemble Clustering for Increasing the Accuracy of the Final Clustering

Clustering algorithms are highly dependent on different factors such as the number of clusters, the specific clustering algorithm, and the used distance measure. Inspired from ensemble classification, one approach to reduce the effect of these factors on the final clustering is ensemble clustering. Since weighting the base classifiers has been a successful idea in ensemble classification, in th...

Generation of Weighting Triangles Associated with Aggregation Functions

In this work, we present several ways to obtain different types of weighting triangles, due to these types characterize some interesting properties of Extended Ordered Weighted Averaging operators, EOWA, and Extended Quasi–linear Weighted Mean, EQLWM, as well as of their reverse functions. We show that any quantifier determines an EOWA operator which is also an Extended Aggregation Function, EA...