A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor

A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor

This study introduces the hybrid of the Bayesian optimization algorithm and support vector regression (BOA-SVR) models to predict the removal of aerobic organic (total chemical oxygen demand, COD) and nitrogen compounds such as total Kjeldahl Nitrogen (TKN), ammonium nitrogen (NH4-N), and nitrate ni...

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Bibliographic Details
Main Authors: Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Digital Chemical Engineering
Subjects:
Nitrogen removal
Municipal wastewater
Gas-liquid-solid circulating fluidized bed (GLSCFB) downer
Bayesian optimization algorithm (BOA)
Support vector regression (SVR)
Online Access:http://www.sciencedirect.com/science/article/pii/S2772508124000504
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