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Uncertainty Quantification for the Required Fossil Fuel Generation in a Smart Grid
conference contribution
posted on 2021-01-01, 00:00 authored by Hussain Mohammed Dipu Kabir, A Khorsavi, M S Rahman, Anwar HosenAnwar Hosen, Saeid NahavandiSaeid NahavandiUncertainty Quantification for the Required Fossil Fuel Generation in a Smart Grid
History
Event
Neural networks. Conference (2021 : Shenzhen, China)Pagination
1 - 8Publisher
IEEELocation
Shenzhen, ChinaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2021-07-18End date
2021-07-22ISSN
2161-4407eISSN
2161-4407ISBN-13
9781665445979Language
engPublication classification
E1 Full written paper - refereedTitle of proceedings
IJCNN 2021 : Proceedings of the 2021 International Joint Conference on Neural NetworksUsage metrics
Read the peer-reviewed publication
Categories
Keywords
Science & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Hardware & ArchitectureEngineering, Electrical & ElectronicComputer ScienceEngineeringRenewableUncertainty QuantificationNeural NetworkSmart GridHeteroscedastic UncertaintyNONPARAMETRIC PREDICTION INTERVALSMOTION CUEING ALGORITHMFUZZY-LOGICMODELPLATFORM