Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/2346
Title: Artificial intelligence for the evaluation of operational parameters influencing Nitrification and Nitrifiers in an activated sludge process
Authors: Awolusi, Oluyemi Olatunji 
Nasr, Mahmoud 
Kumari, Sheena K. 
Bux, Faizal 
Keywords: Adaptive neuro-fuzzy inference system;Ammonia-oxidizing bacteria;Nitrite-oxidizing bacteria;Operational parameters;Statistical tools
Issue Date: 2016
Publisher: Springer Science+Business Media
Source: Awolusi, O. O. 2016. Artificial intelligence for the evaluation of operational parameters influencing Nitrification and Nitrifiers in an activated sludge process. Environmental Microbiology. 1-15.
Journal: Environmental microbiology (Online) 
Abstract: 
Abstract Nitrification at a full-scale activated sludge plant treating municipal wastewater was monitored over a period of 237 days. A combination of fluorescent in situ hybridiza-tion (FISH) and quantitative real-time polymerase chain reac-tion (qPCR) were used for identifying and quantifying the dominant nitrifiers in the plant. Adaptive neuro-fuzzy infer-ence system (ANFIS), Pearson’s correlati...
URI: http://hdl.handle.net/10321/2346
ISSN: 1462-2912 (print)
1462-2920 (online)
DOI: 10.1007/s00248-016-0739-3
Appears in Collections:Research Publications (Applied Sciences)

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