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Short-Term Load Forecasting by Artificial Intelligent Technologies
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JingZhao,YaoqiDuanandXiaojuanLiu Uncertainty Analysis of Weather Forecast Data for Cooling Load Forecasting Based on the MonteCarloMethod Reprintedfrom:Energies2018,11, 1900,doi:10.3390/en11071900 . . . . . . . . . . . . . . . . . . . 211 BenjaminAuder, JairoCugliari,YannigGoude, Jean-MichelPoggi ScalableClusteringof IndividualElectricalCurves forProfilingandBottom-UpForecasting Reprintedfrom:Energies2018,11, 1893,doi:10.3390/en11071893 . . . . . . . . . . . . . . . . . . . 229 MagnusDahl,AdamBrun,OliverS.KirsebomandGormB.Andresen ImprovingShort-TermHeatLoadForecastswithCalendarandHolidayData Reprintedfrom:Energies2018,11, 1678,doi:10.3390/en11071678 . . . . . . . . . . . . . . . . . . . 251 MerganiA.Khairalla,XuNing,NashatT.AL-JalladandMusaabO.El-Faroug Short-TermForecasting for EnergyConsumption through StackingHeterogeneous Ensemble LearningModel Reprintedfrom:Energies2018,11, 1605,doi:10.3390/en11061605 . . . . . . . . . . . . . . . . . . . 267 JiyangWang,YuyangGaoandXuejunChen A Novel Hybrid Interval Prediction Approach Based on Modified Lower Upper Bound Estimation inCombinationwithMulti-Objective Salp SwarmAlgorithm for Short-TermLoad Forecasting Reprintedfrom:Energies2018,11, 1561,doi:10.3390/en11061561 . . . . . . . . . . . . . . . . . . . 288 XingZhang Short-TermLoadForecastingforElectricBusChargingStationsBasedonFuzzyClusteringand LeastSquaresSupportVectorMachineOptimizedbyWolfPackAlgorithm Reprintedfrom:Energies2018,11, 1449,doi:10.3390/en11061449 . . . . . . . . . . . . . . . . . . . 318 WeiSunandChongchongZhang AHybridBA-ELMModelBasedonFactorAnalysisandSimilar-DayApproachforShort-Term LoadForecasting Reprintedfrom:Energies2018,11, 1282,doi:10.3390/en11051282 . . . . . . . . . . . . . . . . . . . 336 YunyanLi,YuanshengHuangandMeimeiZhang Short-TermLoadForecasting for Electric VehicleCharging StationBased onNiche Immunity LionAlgorithmandConvolutionalNeuralNetwork Reprintedfrom:Energies2018,11, 1253,doi:10.3390/en11051253 . . . . . . . . . . . . . . . . . . . 354 YixingWang,MeiqinLiu,ZhejingBaoandSenlinZhang Short-Term Load Forecasting with Multi-Source Data Using Gated Recurrent Unit Neural Networks Reprintedfrom:Energies2018,11, 1138,doi:10.3390/en11051138 . . . . . . . . . . . . . . . . . . . 372 ChengdongLi,ZixiangDing, JianqiangYi,YishengLvandGuiqingZhang DeepBeliefNetworkBasedHybridModel forBuildingEnergyConsumptionPrediction Reprintedfrom:Energies2018,11, 242,doi:10.3390/en11010242 . . . . . . . . . . . . . . . . . . . . 391 Ping-HuanKuoandChiou-JyeHuang AHighPrecisionArtificialNeuralNetworksModel forShort-TermEnergyLoadForecasting Reprintedfrom:Energies2018,11, 213,doi:10.3390/en11010213 . . . . . . . . . . . . . . . . . . . . 417 vi
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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