Infilling missing data and outliers for a conventional sewage treatment plant using a self-organizing map: a case study of Kauma Sewage Treatment Plant in Lilongwe, Malawi

Infilling missing data and outliers for a conventional sewage treatment plant using a self-organizing map: a case study of Kauma Sewage Treatment Plant in Lilongwe, Malawi

Data availability is key for modeling of wastewater treatment processes. However, process data are characterized by missing values and outliers. This study applied a self-organizing map (SOM) to fill in missing values and replace outliers in wastewater treatment data from Kauma Sewage Treatment Plan...

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Bibliographic Details
Main Authors: Madalitso H. Mng'ombe, Brighton Austin Chunga, Eddie W. Mtonga, Russel C. G. Chidya, Mphatso Malota
Format: Article
Language:English
Published: IWA Publishing 2023-06-01
Series:H2Open Journal
Subjects:
artificial neural network
data management
sanitation
self-organizing map
wastewater treatment
Online Access:http://h2oj.iwaponline.com/content/6/2/280

Internet

http://h2oj.iwaponline.com/content/6/2/280

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