Using AI and BES/MFC to decrease the prediction time of BOD5 measurement

被引：3

作者：

Medvedev, Ivan ^{[1
]}

Kornaukhova, Mariya ^{[1
]}

Galazis, Christoforos ^{[2
]}

Lorant, Balint ^{[3
]}

Tardy, Gabor Mark ^{[3
]}

Losev, Alexander ^{[1
]}

Goryanin, Igor ^{[4
,5
]}

机构：

[1] Volgograd State Univ, Volgograd, Russia

[2] Imperial Coll London, London, England

[3] Budapest Univ Technol & Econ, Budapest, Hungary

[4] Univ Edinburgh, Edinburgh, Scotland

[5] Okinawa Inst Sci & Technol, Okinawa, Japan

来源：

ENVIRONMENTAL MONITORING AND ASSESSMENT | 2023年 / 195卷 / 09期

关键词：

Neural network; Biochemical Oxygen demand; Biosensor; Microbial fuel cell; MICROBIAL FUEL-CELLS;

D O I：

10.1007/s10661-023-11576-0

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Biochemical oxygen demand (BOD) is one of the most important water/wastewater quality parameters. BOD5 is the amount of oxygen consumed in 5 days by microorganisms that oxidize biodegradable organic materials in an aerobic biochemical manner. The primary objective of this research is to apply microbial fuel cells (MFCs) to reduce the time requirement of BOD5 measurements. An artificial neural network (ANN) has been created, and the predictions we obtained for BOD5 measurements were carried out within 6-24 h with an average error of 7%. The outcomes demonstrated the viability of our AI MFC/BES BOD5 sensor in real-life scenarios.

引用

页数：15

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