Explore the words cloud of the SEE.4C project. It provides you a very rough idea of what is the project "SEE.4C" about.
The following table provides information about the project.
FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
|Coordinator Country||Germany [DE]|
|Total cost||760˙806 €|
|EC max contribution||760˙806 € (100%)|
1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
|Duration (year-month-day)||from 2016-01-01 to 2018-03-31|
Take a look of project's partnership.
|1||FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.||DE (MUNCHEN)||coordinator||330˙000.00|
|2||UNIVERSITAT DE BARCELONA||ES (BARCELONA)||participant||212˙556.00|
|3||UNIVERSITE D'AIX MARSEILLE||FR (Marseille)||participant||201˙125.00|
|4||RTE RESEAU DE TRANSPORT D'ELECTRICITE||FR (PARIS LA DEFENSE CEDEX)||participant||17˙125.00|
Fast, accurate forecasting of spatiotemporal data is needed in critical industrial domains such as energy (prediction of spatiotemporal patterns in renewable generation, usage and traffic) as well as in public policy. The task is so challenging in scale and scope however as to have been confined mainly to research, while past prize competitions have been limited to forecasts of single dimensional values. Building on our proven success in numerous prize-driven past data challenges, attracting hundreds of participants, we aim to compile and test data grounded on large-scale open European datasets and including specially prepared grid traffic data from Europe’s largest Transportation System Operator. The competition evaluates forecasting algorithms on a cloud platform, tracking accuracy and computational efficiency. Emphasizing cross-specialization knowledge transfer and openness to novel technologies which may spring from different subsectors, we aim to build a platform allowing for coopetitions: the ad-hoc coalescence of competing teams during a challenge aimed at forming sustainable partnerships past the prize scheme itself. We will provide comprehensive documentation for a freely extensible open-source cloud-based specialized computing platform (assembling existing, well tested tools) allowing automated evaluation and feedback as in our latest competitions, but scaled to big data needs. We aim to test this platform and provide baseline results in a smaller scale mini-competition (hackathon). Thus we shall lay the groundwork for a larger prize competition in which evaluation data for predictions may arrive in real or near-real time. We also aim to use our wide contacts with industry, domain and data experts and past participants and winners in order to organize focused meetings of panels to refine value chains in data and algorithms as well as conference workshops, talks and newsletters dedicated to widely advertising challenges to past and new participants.
|Data Donor Guidelines||Documents, reports||2019-05-30 13:16:02|
|Hackathon Proceedings||Documents, reports||2019-05-30 13:16:00|
Take a look to the deliverables list in detail: detailed list of SEE.4C deliverables.
|year||authors and title||journal||last update|
Florin Popescu, Stephane Ayache, Sergio Escalera, Xavier BarÃ³ SolÃ©, Cecile Capponi, Patrick
Panciatici, and Isabelle Guyon
From geospatial observations of ocean currents to causalpredictors of spatio-economic activity using computer vision and machine learning
published pages: , ISSN: , DOI:
|Geophysical Research Abstracts, vol. 18||2019-06-18|
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The information about "SEE.4C" are provided by the European Opendata Portal: CORDIS opendata.