
Energy Management-Collective and Computational Intelligence with Theory and Applications
Springer (Publisher)
Published on 14. December 2018
Book
Paperback/Softback
XV, 554 pages
978-3-030-09299-3 (ISBN)
Description
This book presents a selection of recently developed collective and computational intelligence techniques, which it subsequently applies to energy management problems ranging from performance analysis to economic analysis, and from strategic analysis to operational analysis, with didactic numerical examples. As a form of intelligence emerging from the collaboration and competition of individuals, collective and computational intelligence addresses new methodological, theoretical, and practical aspects of complex energy management problems. The book offers an excellent reference guide for practitioners, researchers, lecturers and postgraduate students pursuing research on intelligence in energy management. The contributing authors are recognized researchers in the energy research field.
More details
Series
Edition
Softcover Reprint of the Original 1st 2018 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
69 farbige Abbildungen, 52 s/w Abbildungen
XV, 554 p. 121 illus., 69 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 31 mm
Weight
855 gr
ISBN-13
978-3-030-09299-3 (9783030092993)
DOI
10.1007/978-3-319-75690-5
Schweitzer Classification
Other editions
Additional editions

Cengiz Kahraman | Gülgün Kayakutlu
Energy Management-Collective and Computational Intelligence with Theory and Applications
Book
04/2018
Springer
€160.49
Shipment within 10-15 days
Content
Complexity in Energy Systems.- Fuzzy Sets Applications in Complex Energy Systems: A literature review.- Fuzzy Forecasting Methods for Energy Planning.- Wind Energy Investment Analyses Based on Fuzzy Sets.- Strategic Analysis of Solar Energy Pricing Process with Hesitant Fuzzy Cognitive Map.- Electrical Vehicle charging coordination algorithms framework.