New tool for evaluation of performance of wastewater treatment plant:: Artificial neural network

被引：40

作者：

Çinar, Ö ^{[1
]}

机构：

[1] Kahramanmaras Sutcu Imam Univ, Dept Environm Engn, Kahramanmaras, Turkey

来源：

PROCESS BIOCHEMISTRY | 2005年 / 40卷 / 09期

关键词：

Pelham wastewater treatment plant; artificial neural network; Kohonen self-organizing feature maps;

D O I：

10.1016/j.procbio.2005.01.012

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Kohonen self-organizing feature maps, a method of artificial intelligence method, was used to classify operational data of Pelham wastewater treatment plant and to determine the reasons for high effluent concentrations of biological oxygen demand (BOD), total suspended solids (TSS) and fecal coliform in this study. The reasons causing high effluent concentrations of these parameters were low pH in the biological reactor and high solid retention time (SRT). (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：2980 / 2984

页数：5

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