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Titlebook: Energy Management—Collective and Computational Intelligence with Theory and Applications; Cengiz Kahraman,Gülgün Kayakutlu Book 2018 Sprin

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書(shū)目名稱Energy Management—Collective and Computational Intelligence with Theory and Applications
編輯Cengiz Kahraman,Gülgün Kayakutlu
視頻videohttp://file.papertrans.cn/311/310327/310327.mp4
概述Presents cases and examples of collective and computational intelligence applications in the energy industry.Includes collective and computational intelligence techniques such as ant colony optimizati
叢書(shū)名稱Studies in Systems, Decision and Control
圖書(shū)封面Titlebook: Energy Management—Collective and Computational Intelligence with Theory and Applications;  Cengiz Kahraman,Gülgün Kayakutlu Book 2018 Sprin
描述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.
出版日期Book 2018
關(guān)鍵詞Collective Intelligence for Energy; Computational Intelligence for Energy; Energy Planning; Energy Fore
版次1
doihttps://doi.org/10.1007/978-3-319-75690-5
isbn_softcover978-3-030-09299-3
isbn_ebook978-3-319-75690-5Series ISSN 2198-4182 Series E-ISSN 2198-4190
issn_series 2198-4182
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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https://doi.org/10.1007/978-3-642-93598-5e factors are obtained. The results indicate that the factors affecting solar energy systems have an important effect in determining the solar energy price. The solar energy price adapts to the general energy price market in the long term.
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,Erratum to: Die prim?ren Mineralien,ptimizing for low power consumption of such computing systems. We present two computational techniques of resolution: an exact algorithm based on Branch-and-Cut and a meta-heuristic based on Genetic Algorithm. While the exact algorithm combines a branch-and-cut strategy with response time based sche
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