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Parameter Identification of an Activated Sludge Wastewater Treatment Process Based on Particle Swarm Optimization Method

机译:基于粒子群算法的活性污泥废水处理工艺参数辨识

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摘要

The current paper is entirely devoted to show the applicability of Particle Swarm Optimization (PSO) algorithm as a parameter identification method for a representative model of an Activated Sludge Wastewater Treatment Process (ASWWTP) with alternating phases. The model of identification is composed of two linear submodels: one for the aerobic phase and the other for the anoxic phase. In order to prove the efficiency of the proposed method, its performance is compared with another classical method called Simplex Search Algorithm (SSA) as well as with the experimental data.
机译:本篇论文完全致力于展示粒子群优化(PSO)算法作为交替阶段的活性污泥废水处理工艺(ASWWTP)代表性模型的参数识别方法的适用性。识别模型由两个线性子模型组成:一个用于有氧阶段,另一个用于缺氧阶段。为了证明该方法的有效性,将其性能与另一种称为单纯形搜索算法(SSA)的经典方法以及实验数据进行了比较。

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