The evaluation of wastewater treatment plant performance: a data mining approach

被引：4

作者：

Aldaghi, Tahmineh ^{[1
]}

Javanmard, Shima ^{[1
]}

机构：

[1] Tarbiat Modares Univ, Tehran, Iran

来源：

JOURNAL OF ENGINEERING DESIGN AND TECHNOLOGY | 2023年 / 21卷 / 06期

关键词：

Data mining; Wastewater treatment plant; Effluents; Removed efficiency; Neural network; Regression; Artificial intelligence; Environmental; Quality and health and safety issues; ARTIFICIAL NEURAL-NETWORKS; SUSPENDED-SOLIDS; PREDICTION; MANAGEMENT; MODEL;

D O I：

10.1108/JEDT-07-2021-0394

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Purpose This paper aims to evaluate the performance of the Mashhad No. 5 wastewater treatment plant (WWTP) using a combination of data mining (regression) algorithms and artificial neural networks. Design/methodology/approach In this research, the performance of WWTP located in Mashhad, Iran, has been evaluated using two data mining models, neural network and regression model. Findings The proposed model has the potential of implementing in other WWTPs in Iran or other countries. Originality/value The authors would also like to thank Mashhad No.5 WWTP for data access.

引用

页码：1785 / 1802

页数：18

共 28 条

[11] Activated sludge wastewater treatment plant modelling and simulation: state of the art
Gernaey, KV
van Loosdrecht, MCM
Henze, M
Lind, M
Jorgensen, SB
[J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2004, 19 (09) : 763 - 783
[12] Prediction of effluent concentration in a wastewater treatment plant using machine learning models
Guo, Hong
Jeong, Kwanho
Lim, Jiyeon
Jo, Jeongwon
Kim, Young Mo
Park, Jong-Pyo
Kim, Joon Ha
Cho, Kyung Hwa
[J]. JOURNAL OF ENVIRONMENTAL SCIENCES, 2015, 32 : 90 - 101
[13] Strategies and best practice for neural network image classification
Kanellopoulos, I
Wilkinson, GG
[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 1997, 18 (04) : 711 - 725
[14] Kuhn M., 2013, Applied Predictive Modeling, V26
[15] A data-mining approach to predict influent quality
Kusiak, Andrew
Verma, Anoop
Wei, Xiupeng
[J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2013, 185 (03) : 2197 - 2210
[16] THE APPLICATION OF NEURAL NETWORKS AND A QUALITATIVE RESPONSE MODEL TO THE AUDITORS GOING-CONCERN UNCERTAINTY DECISION
LENARD, MJ
ALAM, P
MADEY, GR
[J]. DECISION SCIENCES, 1995, 26 (02) : 209 - 227
[17] Metcalf L., 2003, Wastewater Engineering: Treatment and Reuse, VFourth
[18] Neural network prediction model for the methane fraction in biogas from field-scale landfill bioreactors
Ozkaya, Bestamin
Demir, Ahmet
Bilgili, M. Sinan
[J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2007, 22 (06) : 815 - 822
[19] Grey and neural network prediction of suspended solids and chemical oxygen demand in hospital wastewater treatment plant effluent
Pai, T. Y.
Tsai, Y. P.
Lo, H. M.
Tsai, C. H.
Lin, C. Y.
[J]. COMPUTERS & CHEMICAL ENGINEERING, 2007, 31 (10) : 1272 - 1281
[20] 2-GROUP CLASSIFICATION USING NEURAL NETWORKS
PATUWO, E
HU, MY
HUNG, MS
[J]. DECISION SCIENCES, 1993, 24 (04) : 825 - 845

← 1 2 3 →