文章基本信息

标题：Artificial Neural Network Modeling of an Inverse Fluidized Bed Bioreactor
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作者：M Raasimman ; I Govindarajan ; C Karthikeyan 等
期刊名称：Journal of Applied Sciences and Environmental Management
印刷版ISSN：1119-8362
出版年度：2007
卷号：11
期号：2
DOI：10.4314/jasem.v11i2.54991
语种：English
出版社：Department of Pure & Industrial Chemistry, University of Port Harcourt
摘要：The application of neural networks to model a laboratory scale inverse fluidized bed reactor has been studied. A Radial Basis Function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. In the proposed model, the trained neural network represents the kinetics of biological decomposition of pollutants in the reactor. The neural network has been trained with experimental data obtained from an inverse fluidized bed reactor treating the starch industry wastewater. Experiments were carried out at various initial substrate concentrations of 2250, 4475, 6730 and 8910 mg COD/L and at different hydraulic retention times (40, 32, 24, 26 and 8h). It is found that neural network based model has been useful in predicting the system parameters with desired accuracy.