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布谷鸟搜索算法在活性污泥工艺参数辨识中的应用

Cuckoo Search Approach for Parameter Identification of an Activated Sludge Process.

机构信息

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

出版信息

Comput Intell Neurosci. 2018 Jan 28;2018:3476851. doi: 10.1155/2018/3476851. eCollection 2018.

Abstract

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.

摘要

提出了一种混合模型的参数辨识问题。后者描述了用于废水处理的活性污泥工艺的运行。通过最小化模拟和实验数据之间的误差,可以将参数辨识问题视为优化问题。求解类似数学问题的一种新颖且有前途的元启发式方法是布谷鸟搜索算法。它的灵感来自布谷鸟物种的寄生繁殖行为。为了验证所提出算法的有效性和效率,将仿真结果与其他算法进行比较,首先与经典的 Nelder-Mead 算法进行比较,其次与遗传算法和粒子群优化等智能方法进行比较。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a69b/5833157/8a7f23863a1e/CIN2018-3476851.001.jpg

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