A Practical Guide to Averaging Functions
By Gleb Beliakov, Humberto Bustince, Tomasa Calvo. Studies in Fuzziness and Soft Computing, 2015
435 citations recorded by the source corpus.
This book offers an easy-to-use and practice-oriented reference guide to mathematical averages. It presents different ways of aggregating input values given on a numerical scale, and of choosing and/or constructing aggregating functions for specific applications. Building on a previous monograph by Beliakov et al. published by Springer in 2007, it outlines new aggregation methods developed in the interim, with a special focus on the topic of averaging aggregation functions. It examines recent advances in the field, such as aggregation on lattices, penalty-based aggregation and weakly monotone averaging, and extends many of the already existing methods, such as: ordered weighted averaging (OWA), fuzzy integrals and mixture functions. A substantial mathematical background is not called for, as all the relevant mathematical notions are explained here and reported on together with a wealth of graphical illustrations of distinct families of aggregation functions. The authors mainly focus on practical applications and give central importance to the conciseness of exposition, as well as the relevance and applicability of the reported methods, offering a valuable resource for computer scientists, IT specialists, mathematicians, system architects, knowledge engineers and programmers, as well as for anyone facing the issue of how to combine various inputs into a single output value.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/e463bb23c5bb8b4495aad648e29f7eba2d7ee336
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
Citations in the corpus
- A New Softmax Operator for Reinforcement Learning (2016, methodology): “Also, in the point that lie in between the two fixed-points, progress is extremely slow.”