Feature Papers of Forecasting

• Other Authors: Leva, Sonia (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Research & information: general; Direct Normal Irradiance (DNI); IFS/ECMWF; forecast; evaluation; DNI attenuation Index (DAI); bias correction; nowcast; meteorological radar data; optical flow; deep learning; Bates-Granger weights; uniform weights; (REG) ARIMA; ETS; Hodrick-Prescott trend; Google Trends indices; Himalayan region; streamflow forecast verification; persistence; snow-fed rivers; intermittent rivers; costumer relation management; business to business sales prediction; machine learning; predictive modeling; microsoft azure machine-learning service; travel time forecasting; time series; bus service; transit systems; sustainable urban mobility plan; bus travel time; learning curve; forecasting; production cost; cost estimating; semi-empirical model; logistic map; COVID-19; SARS-CoV-2; PV output power estimation; PV-load decoupling; behind-the-meter PV; baseline prediction; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

Summary

Nowadays, 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.

Physical Description

1 electronic resource (186 p.)

ISBN

books978-3-0365-1031-6
9783036510309
9783036510316

Access

Open Access