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- research-articleSeptember 2015
Unsupervised feature selection using swarm intelligence and consensus clustering for automatic fault detection and diagnosis in Heating Ventilation and Air Conditioning systems
Applied Soft Computing (APSC), Volume 34, Issue CSeptember 2015, Pages 402–425https://doi.org/10.1016/j.asoc.2015.05.030Graphical abstractDisplay Omitted HighlightsOur algorithm aims to improve the feature quality in general fault diagnosis system.The algorithm filters out redundant features using consensus evolutionary clustering.The algorithm was tested on the ASHRAE-...
