Novel Uncertainty-Aware Deep Neuroevolution Algorithm to Quantify Tidal Forecasting
Version 2 2024-06-06, 03:19
Version 1 2023-02-28, 03:43
journal contribution
posted on 2024-06-06, 03:19 authored by SMJ Jalali, S Ahmadian, MK Noman, Abbas KhosraviAbbas Khosravi, SMS Islam, F Wang, JPS CatalaoNovel Uncertainty-Aware Deep Neuroevolution Algorithm to Quantify Tidal Forecasting
History
Journal
IEEE Transactions on Industry ApplicationsVolume
58Pagination
3324-3332Location
CANADA, VancouverISSN
0093-9994eISSN
1939-9367Language
EnglishPublication classification
C1 Refereed article in a scholarly journalIssue
3Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCUsage metrics
Categories
No categories selectedKeywords
Science & TechnologyTechnologyEngineering, MultidisciplinaryEngineering, Electrical & ElectronicEngineeringPredictive modelsForecastingUncertaintyHarmonic analysisDeep learningTrainingPrediction algorithmsDeep neuroevolution (DNE)tidal current forecastinguncertainty quantificationNEURAL-NETWORKMODELLOAD
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC