GECCO Industrial Challenge 2015 Dataset: A heating system dataset for the 'Recovering missing information in heating system operating data' competition at the Genetic and Evolutionary Computation Conference 2015, Madrid, Spain (Q9514)

Dataset of the Industrial Challenge: Recovering missing information in heating system operating data competition hosted atThe Genetic and Evolutionary Computation Conference (GECCO)July 11th-15th 2015, Madrid, Spain The task of thecompetition wasto recover (impute) missing information in heating system operation time series. Included in zenodo: - dataset of heating system operational time series with missing values - additional material and descriptions provided for the competition The competition was organized by: M. Friese, A. Fischbach, C. Schlitt, T. Bartz-Beielstein (TH Kln) The dataset was providedby: Major German heating systems supplier (S. Moritz) Industrial Challenge: Recovering missing information in heating system operating data The Industrial Challenge will be held in the competition session at the Genetic and Evolutionary Computation Conference. It poses difficult real-world problems provided by industry partners from various fields. Highlights of the Industrial Challenge include interesting problem domains, real-world data and realistic quality measurement Overview In times of accelerating climate change and rising energy costs, increasing energy efficiency and reducing expenses becomes a high priority goal for businesses and private households alike. Modern heating systems record detailed operating data and report this data to a central system. Here, the operating data can be correlated and analyzed to detect potential optimization opportunities or anomalies like unusually high energy consumption. Due to various difficulties this data might be incomplete which makes accurate forecasting even harder. Goal of the GECCO 2015 Industrial Challenge is to develop capable procedures to recover missing information in heating system operating data. Adequate recovery of the missing data enables more accurate forecastings which allow for intelligent control of the heating systems, and therefore contributes to a positive energy balance and reduced expenses. Submission deadline: June 22, 2015 Official Webpage: www.spotseven.de/gecco-challenge/gecco-challenge-2015/