Abstract
The monitoring of surface water quality is insufficient in Mexico due to the limited water monitoring stations. The main monitoring parameter to evaluate surface water quality is the biochemical oxygen demand. This parameter estimates the biodegradable organic matter present in the water. Concentrations above 30 mg/l indicates a high level of contamination by domestic and industrial waste. Therefore, the aim of this work to provide a reference to the conventional process of determining biochemical oxygen demand using machine learning. The database used was collected by the National Water Commission (CONAGUA). Pearson’s correlation and Forward Selection techniques were applied to identify the parameters with the most important contribution to prediction of biochemical oxygen demand. Two groups were formed and used as input to four machine learning algorithms. Random forest algorithm obtained the best performance. Group 1 and 2 of parameters obtained a 0.76 and 0.75 coefficient of determination respectively. This allows choosing an adequate group of parameters that can be determined with the chemical analysis instruments available in the study area.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Creators: | Creators Email / ID Num. Maximiliano, Guzmán-Fernández maxguzman1@hotmail.com Misael, Zambrano-de la Torre misaelzambrano1997@gmail.com Claudia, Sifuentes-Gallardo clauger17@gmail.com Oscar, Cruz-Dominguez racso_zurc@hotmail.com Carlos, Bautista-Capetillo baucap@uaz.edu.mx Juan, Badillo-de Loera l_badillo@uaz.edu.mx Efrén, González Ramírez gonzalezefren@uaz.edu.mx Héctor, Durán-Muñoz hectorduranm@hotmail.com |
Subjects: | T Technology > TP Chemical technology > Biotechnology T Technology > TP Chemical technology > Biotechnology > Biochemical engineering. Bioprocess engineering |
Divisions: | Universiti Teknologi MARA, Kedah > Sg Petani Campus |
Journal or Publication Title: | International Conference on Computing, Mathematics and Statistics |
Event Title: | e-Proceedings of the 5th International Conference on Computing, Mathematics and Statistics (iCMS 2021) |
Event Dates: | 4-5 August 2021 |
Page Range: | pp. 428-435 |
Keywords: | Machine learning, biochemical oxygen demand, Mexican surface waters |
Date: | 2021 |
URI: | https://ir.uitm.edu.my/id/eprint/56242 |