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  • 标题:Cuckoo Search Approach for Parameter Identification of an Activated Sludge Process
  • 本地全文:下载
  • 作者:Intissar Khoja ; Taoufik Ladhari ; Faouzi M’sahli
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2018
  • 卷号:2018
  • DOI:10.1155/2018/3476851
  • 出版社:Hindawi Publishing Corporation
  • 摘要: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.
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