New approach to predict fecal coliform removal for stormwater biofilter applications
Document Type
Article
Publication Date
1-1-2022
Abstract
Fecal coliform removal using stormwater biofilters is an important aspect of stormwater management. A model that can provide an accurate prediction of fecal coliform removal is essential. Therefore, feedforward backpropagation neural network (FBNN) and adaptive neuro-fuzzy inference system (ANFIS) models were developed using a range of input features, namely grass type, the thickness of biofilter, and initial concentration of E. coli, while the estimated final concentration of E. coli was the output variable. The ANFIS model shows a better overall performance than the FBNN model, as it has a higher R2-value of 0.9874, lower MAE and RMSE values of 3.854 and 6.004 respectively, and a smaller average percentage error of 14.2. Hence, the proposed ANFIS model can be served as an advanced alternative to replace the need for laboratory work. © 2022
Keywords
Artificial intelligence, biofilters, fecal coliform, neural network, stormwater
Divisions
fac_eng,sch_civ
Publication Title
IIUM Engineering Journal
Volume
23
Issue
2
Publisher
International Islamic University Malaysia
Additional Information
Cited by: 0; All Open Access, Gold Open Access