Overview
- Presents cases and examples of collective and computational intelligence applications in the energy industry
- Includes collective and computational intelligence techniques such as ant colony optimization, swarm optimization, simulated annealing, genetic algorithms, neural networks, and fuzzy sets
- Offers essential insights for the investigation and projection of energy plans and schedules using the most recent analytical methods from collective and computational intelligence
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 149)
Buy print copy
About this book
Similar content being viewed by others
Keywords
Table of contents (24 chapters)
-
Introduction
-
Economic Analysis
-
Strategic Analysis
-
Operational Analysis
Editors and Affiliations
Bibliographic Information
Book Title: Energy Management—Collective and Computational Intelligence with Theory and Applications
Editors: Cengiz Kahraman, Gülgün Kayakutlu
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-319-75690-5
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-75689-9Published: 04 April 2018
Softcover ISBN: 978-3-030-09299-3Published: 14 December 2018
eBook ISBN: 978-3-319-75690-5Published: 21 March 2018
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XV, 554
Number of Illustrations: 52 b/w illustrations, 69 illustrations in colour
Topics: Computational Intelligence, Energy Policy, Economics and Management, Energy Policy, Economics and Management