https://scholars.lib.ntu.edu.tw/handle/123456789/408267
標題: | Modeling denitrifying sulfide removal process using artificial neural networks | 作者: | Wang A. Liu C. Han H. Ren N. Lee D.-J. |
關鍵字: | Artificial neural networks;Denitrifying sulfide removal systems;EGSB;Modeling | 公開日期: | 2009 | 卷: | 168 | 期: | 2月3日 | 起(迄)頁: | 1274-1279 | 來源出版物: | Journal of Hazardous Materials | 摘要: | The denitrifying sulfide removal (DSR) process has complex interactions between autotrophic and heterotrophic denitrifers; thus, constructing a detailed mechanistic model and proper control architecture is difficult. Artificial neural networks (ANNs) are capable of inferring the complex relationships between input and output process variables without a detailed characterization of the mechanisms governing the process. This work presents a novel ANN that accurately predicts the steady-state performance of an expended granular sludge bed (EGSB)-DSR bioreactor for nitrite denitrification and the complete DSR process. The proposed ANN shows that at a threshold hydraulic retention time (HRT) < 7 h, influent sulfide concentration markedly affects reactor performance. ? 2009 Elsevier B.V. All rights reserved. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/408267 | ISSN: | 03043894 | DOI: | 10.1016/j.jhazmat.2009.03.006 |
顯示於: | 化學工程學系 |
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