My Account Log in

1 option

Choquet Capacities and Fuzzy Integrals / by Gleb Beliakov, Simon James, Jian-Zhang Wu.

Springer Nature - Springer Computer Science eBooks 2026 English International Available online

View online
Format:
Book
Author/Creator:
Beliakov, Gleb.
Series:
Theory and Applications of Computability, In cooperation with the Association Computability in Europe, 2190-6203
Language:
English
Subjects (All):
Computer science.
Integral equations.
Functions, Special.
Theory of Computation.
Integral Equations.
Computer Science Logic and Foundations of Programming.
Special Functions.
Local Subjects:
Theory of Computation.
Integral Equations.
Computer Science Logic and Foundations of Programming.
Special Functions.
Physical Description:
1 online resource (555 pages)
Edition:
1st ed. 2026.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
Summary:
Choquet capacities, which provide the weighting mechanism for the Choquet and other fuzzy integrals, model synergistic and antagonistic interactions between variables by assigning value to all subsets rather than individual inputs. This book provides a detailed overview of the background concepts relating to capacities and their role in fuzzy integration and aggregation, then presents specialised chapters on most recent results in learning, random sampling and optimization that involve Choquet capacities. Topics and features: · Fundamentals of Choquet capacities (fuzzy measures) and their use in modeling importance and interaction between variables · Definitions, properties and mappings between alternative representations that allow capacities and fuzzy integrals to be interpreted and applied in different settings · Capacity learning formulations that allow the diverse types to be elicited from datasets or according to user-specified requirements · Recent findings related to random sampling and optimisation with Choquet integral objectives This book includes illustrative examples and guidance for implementation, including an appendix detailing functions found in the pyfmtools software library. It aims to be useful for practitioners and researchers in decision and data-driven fields, or those who wish to apply these emerging tools to new problems. The authors are all affiliated with the School of Information Technology at Deakin University, Australia. Gleb Beliakov is a professor, Simon James< is an Associate Professor, and Jian-Zhang Wu is a Research Fellow. .
Contents:
Introduction
Types of Capacities
Value and Interaction Indices
Representations
Fuzzy Intergrals
Sparse Capacities
Symmetric Fuzzy Measures: OWA
Learning Capacities
Optimisation Models Based on Fuzzy Integrals
Random Sampling of the Capacities.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
9783031970702
OCLC:
1553136989

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account