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Ant Colony, Bee Colony and Elephant Herd Optimisations for Estimating Aqueous-Phase Adsorption Model Parameters

aUniversity of Mauritius, Mauritius
bShenzhen University, China; Shoolini University & Glocal University, India
cHoneychem Research, New Zealand
dUniversity of Johannesburg, South Africa; Aarhus University, Denmark; Zhejiang Rongsheng Environmental Protection Paper Co. LTD, China; Chandigarh University, India

Artificial Intelligence, Engineering Systems and Sustainable Development

ISBN: 978-1-83753-541-5, eISBN: 978-1-83753-540-8

Publication date: 18 January 2024

Abstract

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

Keywords

Citation

Mudhoo, A., Sharma, G., Chu, K.H. and Sillanpää, M. (2024), "Ant Colony, Bee Colony and Elephant Herd Optimisations for Estimating Aqueous-Phase Adsorption Model Parameters", Fowdur, T.P., Rosunee, S., Ah King, R.T.F., Jeetah, P. and Gooroochurn, M. (Ed.) Artificial Intelligence, Engineering Systems and Sustainable Development, Emerald Publishing Limited, Leeds, pp. 55-66. https://doi.org/10.1108/978-1-83753-540-820241005

Publisher

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Emerald Publishing Limited

Copyright © 2024 Ackmez Mudhoo, Gaurav Sharma, Khim Hoong Chu and Mika Sillanpää. Published under exclusive licence by Emerald Publishing Limited