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Computational Intelligence and Neuroscience
Volume 2018 (2018), Article ID 3476851, 9 pages
Research Article

Cuckoo Search Approach for Parameter Identification of an Activated Sludge Process

Industrial Systems Study and Renewable Energy Unit, National Engineering School of Monastir, University of Monastir, Ibn El Jazzar Street, Skanes, 5019 Monastir, Tunisia

Correspondence should be addressed to Intissar Khoja; moc.liamg@ajohkrassitni

Received 14 July 2017; Revised 5 December 2017; Accepted 20 December 2017; Published 28 January 2018

Academic Editor: Amparo Alonso-Betanzos

Copyright © 2018 Intissar Khoja et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A parameter identification problem for a hybrid model is presented. The latter describes the operation of an activated sludge process used for waste water treatment. Parameter identification problem can be considered as an optimization one by minimizing the error between simulation and experimental data. One of the new and promising metaheuristic methods for solving similar mathematical problem is Cuckoo Search Algorithm. It is inspired by the parasitic brood behavior of cuckoo species. To confirm the effectiveness and the efficiency of the proposed algorithm, simulation results will be compared with other algorithms, firstly, with a classical method which is the Nelder-Mead algorithm and, secondly, with intelligent methods such as Genetic Algorithm and Particle Swarm Optimization approaches.