scholarly journals Prediction of dissolved oxygen in Surma River by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks (ANNs)

2017 ◽  
Vol 29 (2) ◽  
pp. 151-158 ◽  
Author(s):  
A.A. Masrur Ahmed
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dissolved Oxygen ◽  
Chemical Oxygen Demand ◽  
Biochemical Oxygen Demand ◽  
Oxygen Demand ◽  
Artificial Neural ◽  
Surma River

scholarly journals Assessment of the Water Quality Characteristics of Kaduna River Receiving Wastewater Discharges

2019 ◽  
Vol 3 (1) ◽  
pp. 56-61
Author(s):  
H. Garba ◽  
C. A. Elanu
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Chemical Oxygen Demand ◽  
Biochemical Oxygen Demand ◽  
Oxygen Demand ◽  
Domestic Wastewater ◽  
Quality Characteristics ◽  
Chemical Characteristics ◽  
Mean Concentration ◽  
Concentration Levels

An assessment of the chemical characteristics of industrial and domestic wastewater discharges on seven parameters into Kaduna River on a bimonthly basis was carried out. PH, dissolved oxygen (DO), chloride, nitrite, chemical oxygen demand (COD), biochemical oxygen demand (BOD) and iron were analyzed to determine their concentration levels. From the analysis, the highest mean concentration of the parameters were 8.24 of pH, 7.7 mg/l of DO, 233.4 mg/l of chloride, 55.68 mg/l of COD, 27.95 mg/l of nitrite, 122.22 mg/l of BOD, and 17.05 mg/l of iron. After comparing with prescribed standards, it can be concluded that there is evidence of organic and inorganic accumulation of contaminants into River Kaduna.

Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study

2013 ◽  
Vol 20 (12) ◽  
pp. 9006-9013 ◽  
Author(s):  
Davor Antanasijević ◽  
Viktor Pocajt ◽  
Dragan Povrenović ◽  
Aleksandra Perić-Grujić ◽  
Mirjana Ristić
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dissolved Oxygen ◽  
Oxygen Content ◽  
Danube River ◽  
Artificial Neural
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