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Data validation and missing data reconstruction using self-organizing map for water treatment
2011
Neural computing & applications (Print)
Applications in the water treatment domain generally rely on complex sensors located at remote sites. The processing of the corresponding measurements for generating higher-level information such as optimization of coagulation dosing must therefore account for possible sensor failures and imperfect input data. In this paper, selforganizing map (SOM)-based methods are applied to multiparameter data validation and missing data reconstruction in a drinking water treatment. The SOM is a special
doi:10.1007/s00521-011-0526-5
fatcat:hpcbwcx3kjduxa6avoopi4l2zq