New Approach to Predict Fecal Coliform Removal for Stormwater Biofilters Application

Authors

DOI:

https://doi.org/10.31436/iiumej.v23i2.2173

Keywords:

Artificial intelligence, Biofilters, Fecal coliform, Neural network, Stormwater

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.

ABSTRAK: Penyingkiran kolifom tinja menggunakan turas biologi (bioturas) air hujan merupakan aspek penting dalam pengurusan air hujan. Model yang dapat menunjukkan anggaran tepat tentang penyingkiran kolifom tinja adalah penting. Oleh itu, model rangkaian suapan neural perambatan belakang (FBNN) dan sistem adaptasi inferen neuro-fuzi (ANFIS) telah dibentukkan menggunakan pelbagai ciri input, iaitu jenis rumput, ketebalan bioturas dan kepekatan awal E. coli, manakala anggaran kepekatan akhir bagi E. coli merupakan hasil pembolehubah. Model ANFIS menunjukkan peningkatan keseluruhan yang lebih baik berbanding model FBNN, kerana ia mempunyai nilai R2 yang lebih tinggi iaitu 0.9874, nilai MAE dan RMSE yang lebih rendah iaitu sebanyak 3.854 dan 6.004 masing-masing, dan ralat peratusan purata yang lebih kecil sebanyak 14.2%. Oleh itu, model ANFIS yang dicadangkan boleh dijadikan alternatif awal bagi menggantikan keperluan kerja makmal.

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Author Biographies

Sai Hin Lai, University of Malaya

Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia

Chun Hooi Bu, University of Malaya

Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia

Ren Jie Chin, Universiti Tunku Abdul Rahman

Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman

Xiang Ting Goh, University of Malaya

Department of Parasitology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia

Fang Yenn Teo, University of Nottingham (Malaysia Campus)

Department of Civil Engineering, Faculty of Engineering, University of Nottingham (Malaysia Campus), 43500 Semenyih, Malaysia

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Published

2022-07-04

How to Cite

Lai, S. H., Bu, C. H., Chin, R. J., Goh, X. T., & Teo, F. Y. (2022). New Approach to Predict Fecal Coliform Removal for Stormwater Biofilters Application. IIUM Engineering Journal, 23(2), 45–58. https://doi.org/10.31436/iiumej.v23i2.2173

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Section

Civil and Environmental Engineering

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