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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.

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 --- Bates-Granger weights --- Hodrick-Prescott trend

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This book focuses on fundamental and applied research on forecasting methods and analyses on how forecasting can affect a great number of fields, spanning from Computer Science, Engineering, and Economics and Business to natural sciences. Forecasting applications are increasingly important because they allow for improving decision-making processes by providing useful insights about the future. Scientific research is giving unprecedented attention to forecasting applications, with a continuously growing number of articles about novel forecast approaches being published.

Computer science. --- Computer engineering.

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Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, etc.) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue “Computational Intelligence in Photovoltaic Systems” is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, etc.); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators.

artificial neural network --- online diagnosis --- genetic algorithm --- renewable energy --- unit commitment --- photovoltaic panel --- power forecasting --- metaheuristic --- monitoring system --- embedded systems --- firefly algorithm --- tracking system --- MPPT algorithm --- integrated storage --- day-ahead forecast --- solar radiation --- prototype model --- artificial neural networks --- parameter extraction --- thermal image --- thermal model --- solar cell --- PV cell temperature --- evolutionary algorithms --- uncertainty --- battery --- harmony search meta-heuristic algorithm --- single-diode photovoltaic model --- symbiotic organisms search --- photovoltaics --- tilt angle --- smart photovoltaic system blind --- orientation --- photovoltaic --- particle swarm optimization --- analytical methods --- computational intelligence --- statistical errors --- ensemble methods --- solar photovoltaic --- electrical parameters --- demand response --- metaheuristic algorithm