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Fitting triangular norms to empirical data

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posted on 2005-01-01, 00:00 authored by Gleb BeliakovGleb Beliakov
This chapter discusses some specific tools that can be used to build triangular norms based on a finite number of (possibly noisy) observations. Such problem arises in applications, when observed data (e.g., decision patterns of experts) need to be modelled with a special class of functions, such as triangular norms. We show how this problem can be transformed into a constrained regression problem, and then efficiently solved. We also discuss related operators: uninorms, nullnorms and associative copulas.

History

Chapter number

9

Pagination

262-272

ISBN-13

9780444518149

ISBN-10

0444518142

Edition

1st ed.

Language

eng

Publication classification

B1.1 Book chapter, B Book chapter

Copyright notice

2005, Elsevier

Extent

16

Editor/Contributor(s)

Klement E, Mesiar R

Publisher

Elsevier

Place of publication

Boston, Mass.

Title of book

Logical, algebraic, analytic, and probabilistic aspects of triangular norms

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