Web-based benchmarks for forecasting systems-The ECAST platform

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

  • Robert Ulbricht - , Robotron Datenbank-Software GmbH (Author)
  • Claudio Hartmann - , TUD Dresden University of Technology (Author)
  • Martin Hahmann - , TUD Dresden University of Technology (Author)
  • Hilko Donker - , Robotron Datenbank-Software GmbH (Author)
  • Wolfgang Lehner - , TUD Dresden University of Technology (Author)

Abstract

The role of precise forecasts in the energy domain has changed dramatically. New supply forecasting methods are developed to better address this challenge, but meaningful benchmarks are rare and time-intensive. We propose the ECAST online platform in order to solve that problem. The system's capability is demonstrated on a real-world use case by comparing the performance of different prediction tools.

Details

Original languageEnglish
Title of host publicationSIGMOD '16: Proceedings of the 2016 International Conference on Management of Data
PublisherAssociation for Computing Machinery (ACM), New York
Pages2169-2172
Number of pages4
ISBN (print)978-1-4503-3531-7
Publication statusPublished - 26 Jun 2016
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesMOD: International Conference on Management of Data (SIGMOD)

Conference

Title2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016
Duration26 June - 1 July 2016
CitySan Francisco
CountryUnited States of America

External IDs

ORCID /0000-0001-8107-2775/work/142253566

Keywords

ASJC Scopus subject areas

Keywords

  • Benchmark, Time series forecasting, Transparency