Seite - (000006) - in Short-Term Load Forecasting by Artificial Intelligent Technologies

Special IssueEditors Wei-ChiangHong JiangsuNormalUniversity China Ming-WeiLi HarbinEngineeringUniversity China Guo-FengFan PingdingshanUniversity China EditorialOffice MDPI St.Alban-Anlage66 4052Basel,Switzerland This isareprintofarticles fromtheSpecial Issuepublishedonline in theopenaccess journalEnergies (ISSN1996-1073)from2018to2019(availableat: https://www.mdpi.com/journal/energies/special issues/Short TermLoad Forecasting) For citationpurposes, cite each article independently as indicatedon the article pageonline andas indicatedbelow: LastName, A.A.; LastName, B.B.; LastName, C.C.Article Title. Journal Name Year,Article Number, PageRange. ISBN978-3-03897-582-3 (Pbk) ISBN978-3-03897-583-0 (PDF) c© 2019 by the authors. Articles in this book areOpenAccess and distributed under theCreative Commons Attribution (CC BY) license, which allows users to download, copy and build upon publishedarticles,aslongastheauthorandpublisherareproperlycredited,whichensuresmaximum disseminationandawider impactofourpublications. ThebookasawholeisdistributedbyMDPIunderthetermsandconditionsoftheCreativeCommons licenseCCBY-NC-ND.