Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
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radiance scene files and metric results generated from high quality referece images for an office building near LAX. contents of lci_tempate.tar.gz: ALLSKIES: 4294 sky conditions generated by write_skydefs.py based on LAX.epw, all ...
In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real ...
The SARS-CoV-2 outburst in March 2020 has led to the lockdown of several countries across the world. Mobility restrictions have been constantly put into action and reversed to find the trade-off between minimizing the number of infections and death and mit ...
Thunderstorms represent a major hazard for flights, as they compromise the safety of both the airframe and the passengers. To address trajectory planning under thunderstorms, three variants of the scenario-based rapidly exploring random trees (SB-RRTs) are ...
The quantification of population-level health behaviors is crucial for guiding public health policy. However, traditional methods for measuring such health behaviors have several short- comings. In recent years social media data has been successfully used ...
Accurate building electricity load forecasts play a major role in the energy transition, as they facilitate flexibility deployment, grid stability and overall reduce costs and CO2 emissions. This research leaverages forecasting and reconciliation of tempor ...
Dynamic network-level models directly addressing ride-sourcing services can be useful for the development of efficient traffic management strategies both for city and company operators. Recent developments presented models under equilibrium situations for ...
Medium-range numerical weather prediction (NWP) is crucial to human activities. Reliable weather forecasts allow better resource management and are essential for disaster preparation. Modern NWP models provide accurate medium-range forecasts, but they requ ...
The study of how people schedule their daily activities is of interest in the context of transport demand forecasting using activity based-models, where activity schedules are generated in order to estimate the trip demand they produce. Machine learning ha ...
Convective weather and its inherent uncertainty constitute one of the major challenges in the air traffic management (ATM) system, entailing both safety hazards and economic losses. In the present work, we propose a stochastic algorithm for trajectory plan ...