Fuzzy collective intelligence for performance measurement in energy systems

Cengiz Kahraman; Sezi Çevik Onar; Basar Oztaysi

doi:10.1007/978-3-319-75690-5_22

Fuzzy collective intelligence for performance measurement in energy systems

Cengiz Kahraman^*, Sezi Çevik Onar, Basar Oztaysi

^*Corresponding author for this work

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Citation (Scopus)

Abstract

Collective intelligence (CI) means that a group of people or animals can solve problems efficiently and offer greater insight and a better answer than any individual could provide. Fuzzy sets have been integrated with collective intelligence techniques in order to allow uncertain, vague imprecise and incomplete information to be incorporated to the CI models. The fuzzy CI techniques have been rarely used in the solution of energy problems even they still present new research opportunities to researchers. This chapter gives the results of the literature review on fuzzy CI research for energy systems.

Original language	English
Title of host publication	Studies in Systems, Decision and Control
Publisher	Springer International Publishing
Pages	497-517
Number of pages	21
DOIs	https://doi.org/10.1007/978-3-319-75690-5_22
Publication status	Published - 2018

Publication series

Name	Studies in Systems, Decision and Control
Volume	149
ISSN (Print)	2198-4182
ISSN (Electronic)	2198-4190

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.

Keywords

Collective intelligence
Energy systems
Fuzzy sets
Particle swarm optimization
Performance

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10.1007/978-3-319-75690-5_22

Cite this

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abstract = "Collective intelligence (CI) means that a group of people or animals can solve problems efficiently and offer greater insight and a better answer than any individual could provide. Fuzzy sets have been integrated with collective intelligence techniques in order to allow uncertain, vague imprecise and incomplete information to be incorporated to the CI models. The fuzzy CI techniques have been rarely used in the solution of energy problems even they still present new research opportunities to researchers. This chapter gives the results of the literature review on fuzzy CI research for energy systems.",

keywords = "Collective intelligence, Energy systems, Fuzzy sets, Particle swarm optimization, Performance",

author = "Cengiz Kahraman and {{\c C}evik Onar}, Sezi and Basar Oztaysi",

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AU - Çevik Onar, Sezi

AU - Oztaysi, Basar

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AB - Collective intelligence (CI) means that a group of people or animals can solve problems efficiently and offer greater insight and a better answer than any individual could provide. Fuzzy sets have been integrated with collective intelligence techniques in order to allow uncertain, vague imprecise and incomplete information to be incorporated to the CI models. The fuzzy CI techniques have been rarely used in the solution of energy problems even they still present new research opportunities to researchers. This chapter gives the results of the literature review on fuzzy CI research for energy systems.

KW - Collective intelligence

KW - Energy systems

KW - Fuzzy sets

KW - Particle swarm optimization

KW - Performance

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ER -

Fuzzy collective intelligence for performance measurement in energy systems

Abstract

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Keywords

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