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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.

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 --- 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

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This Special Issue, consisting of 14 papers, presents the latest findings concerning both numerical and experimental investigations. Their aim is to achieve a reduction in pollutant emissions, as well as an improvement in fuel economy and performance, for internal combustion engines. This will provide readers with a comprehensive, unbiased, and scientifically sound overview of the most recent research and technological developments in this field. More specific topics include: 3D CFD detailed analysis of the fuel injection, combustion and exhaust aftertreatments processes, 1D and 0D, semi-empirical, neural network-based control-oriented models, experimental analysis and the optimization of both conventional and innovative combustion processes.

History of engineering & technology --- homogeneous charge compression ignition (HCCI) --- exhaust gas recirculation (EGR) --- dual-fuel --- dimethyl ether (DME) --- exhaust emission --- co-combustion --- dual fuel --- combustion stability --- coefficient of variation of IMEP --- probability density of IMEP --- 0D model --- predictive model --- tumble --- turbulent intensity --- spark-ignition engine --- engine geometry --- AdBlue® injection --- large eddy simulation --- Eulerian–Lagrangian approach --- thermal decomposition --- wall–film formation --- conversion efficiency --- hybrid electric vehicle --- real driving emissions --- fuel consumption --- vehicle performance --- electric supercharger --- Lambda-1 engine --- 48 V Mild Hybrid --- electrically assisted turbocharger --- variable geometry turbocharger-exhaust gas recirculation --- oxygen concentration --- active disturbance rejection control --- model-based --- control --- diesel engine --- ANN --- physics-based model --- semi-empirical model --- CNG --- diesel fuel --- dual fuel engine --- rate of heat release --- ignition delay --- burn duration --- exhaust gas emission --- camless --- electromagnetic variable valve train --- magnetorheological buffer --- soft landing --- solenoid injectors --- indirect-acting piezoelectric injectors --- direct-acting piezoelectric injectors --- engine-out emissions --- combustion noise --- diesel engines --- pollutant emission reduction --- mixing process --- advanced injection strategy --- varying injection rate --- engine torque estimation --- GDI engines --- extended state observer --- online performance --- torque --- nitrogen oxide emissions --- model-based control --- engines --- numerical simulation --- pollutant emissions prediction --- computational fluid dynamics --- homogeneous charge compression ignition (HCCI) --- exhaust gas recirculation (EGR) --- dual-fuel --- dimethyl ether (DME) --- exhaust emission --- co-combustion --- dual fuel --- combustion stability --- coefficient of variation of IMEP --- probability density of IMEP --- 0D model --- predictive model --- tumble --- turbulent intensity --- spark-ignition engine --- engine geometry --- AdBlue® injection --- large eddy simulation --- Eulerian–Lagrangian approach --- thermal decomposition --- wall–film formation --- conversion efficiency --- hybrid electric vehicle --- real driving emissions --- fuel consumption --- vehicle performance --- electric supercharger --- Lambda-1 engine --- 48 V Mild Hybrid --- electrically assisted turbocharger --- variable geometry turbocharger-exhaust gas recirculation --- oxygen concentration --- active disturbance rejection control --- model-based --- control --- diesel engine --- ANN --- physics-based model --- semi-empirical model --- CNG --- diesel fuel --- dual fuel engine --- rate of heat release --- ignition delay --- burn duration --- exhaust gas emission --- camless --- electromagnetic variable valve train --- magnetorheological buffer --- soft landing --- solenoid injectors --- indirect-acting piezoelectric injectors --- direct-acting piezoelectric injectors --- engine-out emissions --- combustion noise --- diesel engines --- pollutant emission reduction --- mixing process --- advanced injection strategy --- varying injection rate --- engine torque estimation --- GDI engines --- extended state observer --- online performance --- torque --- nitrogen oxide emissions --- model-based control --- engines --- numerical simulation --- pollutant emissions prediction --- computational fluid dynamics

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This Special Issue, consisting of 14 papers, presents the latest findings concerning both numerical and experimental investigations. Their aim is to achieve a reduction in pollutant emissions, as well as an improvement in fuel economy and performance, for internal combustion engines. This will provide readers with a comprehensive, unbiased, and scientifically sound overview of the most recent research and technological developments in this field. More specific topics include: 3D CFD detailed analysis of the fuel injection, combustion and exhaust aftertreatments processes, 1D and 0D, semi-empirical, neural network-based control-oriented models, experimental analysis and the optimization of both conventional and innovative combustion processes.

History of engineering & technology --- homogeneous charge compression ignition (HCCI) --- exhaust gas recirculation (EGR) --- dual-fuel --- dimethyl ether (DME) --- exhaust emission --- co-combustion --- dual fuel --- combustion stability --- coefficient of variation of IMEP --- probability density of IMEP --- 0D model --- predictive model --- tumble --- turbulent intensity --- spark-ignition engine --- engine geometry --- AdBlue® injection --- large eddy simulation --- Eulerian–Lagrangian approach --- thermal decomposition --- wall–film formation --- conversion efficiency --- hybrid electric vehicle --- real driving emissions --- fuel consumption --- vehicle performance --- electric supercharger --- Lambda-1 engine --- 48 V Mild Hybrid --- electrically assisted turbocharger --- variable geometry turbocharger-exhaust gas recirculation --- oxygen concentration --- active disturbance rejection control --- model-based --- control --- diesel engine --- ANN --- physics-based model --- semi-empirical model --- CNG --- diesel fuel --- dual fuel engine --- rate of heat release --- ignition delay --- burn duration --- exhaust gas emission --- camless --- electromagnetic variable valve train --- magnetorheological buffer --- soft landing --- solenoid injectors --- indirect-acting piezoelectric injectors --- direct-acting piezoelectric injectors --- engine-out emissions --- combustion noise --- diesel engines --- pollutant emission reduction --- mixing process --- advanced injection strategy --- varying injection rate --- engine torque estimation --- GDI engines --- extended state observer --- online performance --- torque --- nitrogen oxide emissions --- model-based control --- engines --- numerical simulation --- pollutant emissions prediction --- computational fluid dynamics