采用厌氧混合式反应器进行青霉素 G 废水的生物降解实验及自适应神经模糊推理系统建模。
Experiments and ANFIS modelling for the biodegradation of penicillin-G wastewater using anaerobic hybrid reactor.
机构信息
Department of Technology, Annamalai University, Annamalai Nagar 608 002, Tamil Nadu, India.
出版信息
Bioresour Technol. 2011 May;102(9):5492-7. doi: 10.1016/j.biortech.2011.01.085. Epub 2011 Mar 5.
The performance of an anaerobic hybrid reactor (AHR) for treating penicillin-G wastewater was investigated at the ambient temperatures of 30-35°C for 245 days in three phases. The experimental data were analysed by adopting an adaptive network-based fuzzy inference system (ANFIS) model, which combines the merits of both fuzzy systems and neural network technology. The statistical quality of the ANFIS model was significant due to its high correlation coefficient R(2) between experimental and simulated COD values. The R(2) was found to be 0.9718, 0.9268 and 0.9796 for the I, II and III phases, respectively. Furthermore, one to one correlation among the simulated and observed values was also observed. The results showed the proposed ANFIS model was well performed in predicting the performance of AHR.
采用自适应网络模糊推理系统（ANFIS）模型对青霉素 G 废水在 30-35°C 环境温度下运行的厌氧混合反应器（AHR）的性能进行了 245 天的研究。该模型结合了模糊系统和神经网络技术的优点。实验数据的分析结果表明，由于实验和模拟 COD 值之间的相关系数 R（2）很高，因此 ANFIS 模型的统计质量非常显著。对于 I、II 和 III 阶段，R（2）分别为 0.9718、0.9268 和 0.9796。此外，还观察到模拟值与观察值之间存在一一对应关系。结果表明，所提出的 ANFIS 模型在预测 AHR 的性能方面表现良好。
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