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Short-Term Load Forecasting by Artificial Intelligent Technologies
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Energies2018,11, 3433 44. Li,Y.;Huang,Y.;Zhang,M.Short-termloadforecastingforelectricvehiclechargingstationbasedonniche immunity lionalgorithmandconvolutionalneuralnetwork.Energies2018,11, 1253. [CrossRef] 45. Greff,K.; Srivastava,R.K.;Koutník, J.; Steunebrink,B.R.; Schmidhuber, J.LSTM:Asearchspaceodyssey. IEEETrans.NeuralNetw. Learn. Syst. 2017,28, 2222–2232. [CrossRef] [PubMed] 46. Chung, J.;Gulcehre,C.;Cho,K.;Bengio,Y.EmpiricalEvaluationofGatedRecurrentNeuralNetworkson SequenceModeling. arXiv2014, arXiv:1412.3555. 47. Zhan,T.-S.;Chen,S.-J.;Kao,C.-C.;Kuo,C.-L.;Chen, J.-L.;Lin,C.-H.Non-technical lossandpowerblackout detectionunderadvancedmetering infrastructureusingacooperativegamebasedinferencemechanism. IETGener. Transm.Dis. 2016,10, 873–882. [CrossRef] ©2018bytheauthors. LicenseeMDPI,Basel,Switzerland. Thisarticle isanopenaccess articledistributedunder the termsandconditionsof theCreativeCommonsAttribution (CCBY) license (http://creativecommons.org/licenses/by/4.0/). 81
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Short-Term Load Forecasting by Artificial Intelligent Technologies
Title
Short-Term Load Forecasting by Artificial Intelligent Technologies
Authors
Wei-Chiang Hong
Ming-Wei Li
Guo-Feng Fan
Editor
MDPI
Location
Basel
Date
2019
Language
English
License
CC BY 4.0
ISBN
978-3-03897-583-0
Size
17.0 x 24.4 cm
Pages
448
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Category
Informatik
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Short-Term Load Forecasting by Artificial Intelligent Technologies