Lai, Sai Hin and Bu, Chun Hooi and Chin, Ren Jie and Goh, Xiang Ting and Teo, Fang Yenn (2022) New approach to predict fecal coliform removal for stormwater biofilter applications. IIUM Engineering Journal, 23 (2). 45 – 58. ISSN 1511-788X, DOI https://doi.org/10.31436/iiumej.v23i2.2173.
Full text not available from this repository.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
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | Cited by: 0; All Open Access, Gold Open Access |
| Uncontrolled Keywords: | Artificial intelligence; biofilters; fecal coliform; neural network; stormwater |
| Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering Faculty of Engineering > Department of Civil Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 14 Nov 2024 06:27 |
| Last Modified: | 14 Nov 2024 06:27 |
| URI: | http://eprints.um.edu.my/id/eprint/43779 |
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