Application of machine learning and deep learning methods to power system problems

• Material Type: 図書
• ISBN: 9783030776954 (print); 9783030776961 (electronic bk.); 3030776964 (electronic bk.)
• ISBN (error code): 9783030776954 (print); 3030776956
• ISSN (series): 1612-1287
• Title: Application of machine learning and deep learning methods to power system problems
• Author/Editor: Morteza Nazari-Heris, Somayeh Asadi, Behnam Mohammadi-Ivatloo, Moloud Abdar, Houtan Jebelli, Milad Sadat-Mohammadi, editors
• Series Title: Power systems
• Title Heading: Power systems, 1860-4676
• Author Heading: Nazari-Heris, Morteza
• Publication, Distribution, etc.: Cham, Switzerland : Springer (出版)
• Publication Date: [2022]
• Publication Date (W3CDTF): 2022
• Extent: ix, 391 pages
• Other physical details: illustrations
• Size: 24 cm
• Place of Publication (Country Code): CH
• Text Language Code: eng
• Content Type: text
• Media Type: unmediated
• Carrier Type: volume
• Subject Heading: Electric power systems--Data processing; Machine learning; Réseaux électriques (Énergie)--Informatique; Apprentissage automatique
• LCC: TK1005
• DDC: 621.310285/63
• NDLC: ND131
• Target Audience: 一般
• Note (General): Includes index
• Collection (particular): 日本関係外国語図書
• Holding library: 国立国会図書館
• Call No.: ND131-D28
• Related Material (DOI): 10.1007/978-3-030-77696-1
• Data Provider (Database): 国立国会図書館 : 国立国会図書館蔵書; https://ndlsearch.ndl.go.jp
• Bibliographic ID (NDL): 031502530; http://id.ndl.go.jp/bib/031502530
• Cataloging Rule: RDA
• Bibliographic Record Category (NDL): 211

• Contents: Chapter 1. Power System Challenges and IssuesChapter 2. Introduction and literature review of power system challenges and issuesChapter 3. Machine lea...
• Summary, etc.: This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent dev...