GECCO Industrial Challenge 2017 Dataset: A water quality dataset for the 'Monitoring of drinking-water quality' competition at the Genetic and Evolutionary Computation Conference 2017, Berlin, Germany. (Q9510)

Dataset of the Industrial Challenge: Monitoring of drinking-water quality competition hosted atThe Genetic and Evolutionary Computation Conference (GECCO)July 15th-19th 2017, Berlin, Germany The task of thecompetition wasto develop an anomaly detection algorithm for a water- and environmental data set. Included in zenodo: - dataset of water quality data - additional material and descriptions provided for the competition The competition was organized by: M. Friese, J. Stork, A. Fischbach, M. Rebolledo, T. Bartz-Beielstein (TH Kln) The dataset was provided and prepared by: Thringer Fernwasserversorgung, IMProvT research project (S. Moritz) Industrial Challenge: Monitoring of drinking-water quality Description: Water covers 71% of the Earths surface and is vital to all known forms of life. The provision of safe and clean drinking water to protect public health is a natural aim. Performing regular monitoring of the water-quality is essential to achieve this aim. Goal of the GECCO 2017 Industrial Challenge is to analyze drinking-water data and to develop a highly efficient algorithm that most accurately recognizes diverse kinds of changes in the quality of our drinking-water. Submission deadline: June 30, 2017 Official webpage: http://www.spotseven.de/gecco-challenge/gecco-challenge-2017/