E3S Web Conf.
Volume 347, 20222nd International Conference on Civil and Environmental Engineering (ICCEE 2022)
|Number of page(s)||8|
|Section||Water and Environmental Engineering|
|Published online||14 April 2022|
Modelling of ammonia nitrogen in river using soft computing techniques
Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, 43000 Kajang, Malaysia
* Corresponding author: email@example.com
Ammonia nitrogen is one of the most hazardous water pollution parameters. It is crucial to monitor the concentration of ammonia nitrogen to minimize ammonia nitrogen pollution in river water. This study aims to develop a reliable model to accurately predict ammonia nitrogen concentration. Langat River was selected as the study area. Two soft computing techniques namely Backpropagation Neural Network (BPNN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were employed for the model development. Different model architectures were developed and evaluated. ANFIS model VI appears as an effective tool to serve the main objective where it has a considerably high coefficient of determination, low mean absolute and root mean squared errors, and small average percentage error. The model has an average percentage error of 23%, indicating it is able to provide an estimation accuracy of at least 77%.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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