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dc.contributor.editorLeva, Sonia
dc.date.accessioned2022-01-11T13:38:27Z
dc.date.available2022-01-11T13:38:27Z
dc.date.issued2021
dc.identifierONIX_20220111_9783036510309_401
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/76666
dc.description.abstractNowadays, forecast applications are receiving unprecedent attention thanks to their capability to improve the decision-making processes by providing useful indications. A large number of forecast approaches related to different forecast horizons and to the specific problem that have to be predicted have been proposed in recent scientific literature, from physical models to data-driven statistic and machine learning approaches. In this Special Issue, the most recent and high-quality researches about forecast are collected. A total of nine papers have been selected to represent a wide range of applications, from weather and environmental predictions to economic and management forecasts. Finally, some applications related to the forecasting of the different phases of COVID in Spain and the photovoltaic power production have been presented.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.otherDirect Normal Irradiance (DNI)
dc.subject.otherIFS/ECMWF
dc.subject.otherforecast
dc.subject.otherevaluation
dc.subject.otherDNI attenuation Index (DAI)
dc.subject.otherbias correction
dc.subject.othernowcast
dc.subject.othermeteorological radar data
dc.subject.otheroptical flow
dc.subject.otherdeep learning
dc.subject.otherBates–Granger weights
dc.subject.otheruniform weights
dc.subject.other(REG) ARIMA
dc.subject.otherETS
dc.subject.otherHodrick–Prescott trend
dc.subject.otherGoogle Trends indices
dc.subject.otherHimalayan region
dc.subject.otherstreamflow forecast verification
dc.subject.otherpersistence
dc.subject.othersnow-fed rivers
dc.subject.otherintermittent rivers
dc.subject.othercostumer relation management
dc.subject.otherbusiness to business sales prediction
dc.subject.othermachine learning
dc.subject.otherpredictive modeling
dc.subject.othermicrosoft azure machine-learning service
dc.subject.othertravel time forecasting
dc.subject.othertime series
dc.subject.otherbus service
dc.subject.othertransit systems
dc.subject.othersustainable urban mobility plan
dc.subject.otherbus travel time
dc.subject.otherlearning curve
dc.subject.otherforecasting
dc.subject.otherproduction cost
dc.subject.othercost estimating
dc.subject.othersemi-empirical model
dc.subject.otherlogistic map
dc.subject.otherCOVID-19
dc.subject.otherSARS-CoV-2
dc.subject.otherPV output power estimation
dc.subject.otherPV-load decoupling
dc.subject.otherbehind-the-meter PV
dc.subject.otherbaseline prediction
dc.subject.othern/a
dc.titleFeature Papers of Forecasting
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-1031-6
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036510309
oapen.relation.isbn9783036510316
oapen.pages186
oapen.place.publicationBasel, Switzerland


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